Projection control method and apparatus, projection device, and storage medium

Abstract

The present application provides a projection control method and apparatus, a projection device, and a storage medium. The method comprises: acquiring a first color feature value, the first color feature value being obtained by projecting a preset pure color image onto a first projection background by means of a projection device; determining a second color feature value of an optical machine picture region in a target image, the target image being obtained by using a camera to photograph the preset pure color image projected onto a second projection background by means of the projection device; acquiring a ratio obtained on the basis of the first color feature value and the second color feature value; and, on the basis of the ratio and brightness loss, determining a target color gain of the projection device in a usage environment, the brightness loss being determined on the basis of the ratio or on the basis of projection display brightness of the projection device. The method can avoid manual adjustment by a user while improving a color restoration effect, thereby reducing or avoiding brightness loss.

Description

A projection control method, apparatus, projection device, and storage medium Technical Field

[0001] This application relates to the field of projection technology, and more specifically, to a projection control method, apparatus, projection device, and storage medium. Background Technology

[0002] Currently, with the continuous development of technology, more and more technological devices are entering people's lives. Among them, projection devices have received widespread attention. Projection devices can project images or videos onto walls or screens, allowing users to view the projected images.

[0003] In real-world use cases, projection devices often face diverse projection backgrounds, such as ordinary walls, standard screens, and walls with varying color differences. These non-white backgrounds often cause color discrepancies in the projected image, severely impacting the user's viewing experience.

[0004] To improve the user viewing experience, many projector manufacturers have incorporated manual color temperature adjustment into their devices. Users can adjust the color temperature to reduce color difference and improve color reproduction. However, the inventors of this application have discovered the following problems: First, manually adjusting the color temperature requires a certain level of expertise, which may be challenging for ordinary users. Second, even with color temperature adjustment, color reproduction remains poor due to differences in wall materials, colors, and other factors. Therefore, how to improve color reproduction while avoiding manual adjustment by the user has become a pressing technical problem.

[0005] Summary of the Invention

[0006] This application provides a projection control method, apparatus, projection device, and storage medium, which can improve color reproduction while avoiding manual adjustments by the user.

[0007] A first aspect provides a projection control method applied to a projection device, the projection device having a built-in camera, the method comprising: acquiring a first color feature value; wherein the first color feature value is obtained by the projection device projecting a preset solid color image onto a first projection background; the first projection background is located in a calibration scene of the projection device; determining a second color feature value of an optical-mechanical image area in a target image; wherein the target image is obtained by the projection device projecting the preset solid color image onto a second projection background and then capturing it using the camera; the second projection background is located in a usage scene of the projection device; acquiring a ratio based on the first color feature value and the second color feature value; determining a target color gain of the projection device in the usage scene based on the ratio and a brightness loss; wherein the brightness loss is determined based on the ratio or based on the projection display brightness of the projection device, the projection display brightness being the display brightness of any image to be projected onto the second projection background by the projection device.

[0008] The above technical solution, because the first color feature value is obtained by projecting a preset pure color image onto a first projection background through a projection device in a calibration scene, where environmental conditions (such as lighting, background color, temperature, etc.) are strictly controlled and standardized to ensure the consistency and accuracy of the calibration process, makes the first color feature value obtained in the calibration scene highly reliable and a precise reference for subsequent comparisons. The second color feature value is obtained by projecting a preset pure color image onto a second projection background through a projection device in the usage scene, maintaining the same preset pure color image for projection as in the calibration scene. This ensures that the variable between the two projections in the calibration and usage scenes is the change in the projection background. Extracting the second color feature value from the optical engine screen area of ​​the target image can accurately filter out the influence of non-optical engine screen areas, allowing the determined second color feature value to accurately reflect the color effect output by the projection device in the usage scene. The ratio obtained based on the first and second color feature values ​​can characterize the color difference between images captured by the camera built into the projection device in the calibration and usage scenes, providing accurate data reference for obtaining the target color gain. Based on the ratio and luminance loss, the target color gain of the projection device in the usage scenario is determined. Luminance loss is taken into account when determining the target color gain, which helps to reduce or avoid potential luminance loss in the image after adjustment with this target color gain. Therefore, it achieves automatic improvement in color reproduction while reducing or avoiding luminance loss.

[0009] In conjunction with the first aspect, in some possible implementations, after obtaining the ratio based on the first color feature value and the second color feature value, the method further includes: determining whether there is a brightness loss between the projected display brightness obtained after correction based on the ratio and the projected display brightness before correction; determining the target color gain of the projected device in the usage scenario based on the ratio and the brightness loss includes: if there is a brightness loss, performing brightness compensation based on the ratio to obtain a target ratio, and using the target ratio as the target color gain of the projected device in the usage scenario; if there is no brightness loss, using the ratio as the target color gain of the projected device in the usage scenario.

[0010] In conjunction with the first aspect, in some possible implementations, the first color feature value includes: the average value of the first red channel, the average value of the first green channel, and the average value of the first blue channel; the second color feature value includes: the average value of the second red channel, the average value of the second green channel, and the average value of the second blue channel; the ratio includes: a first ratio between the average value of the first red channel and the average value of the second red channel, a second ratio between the average value of the first green channel and the average value of the second green channel, and a third ratio between the average value of the first blue channel and the average value of the second blue channel; after obtaining the ratio based on the first color feature value and the second color feature value, the above method... The method further includes: determining that there is no luminance loss when the first ratio, the second ratio, and the third ratio are all greater than or equal to 1; determining that there is luminance loss when the first ratio, the second ratio, or the third ratio is less than 1; determining the target color gain of the projection device in the usage scenario based on the ratios and the luminance loss includes: when the luminance loss is determined to exist, performing luminance compensation based on the ratios to obtain a target ratio, and using the target ratio as the target color gain of the projection device in the usage scenario; when the luminance loss is determined to exist, using the ratio as the target color gain of the projection device in the usage scenario.

[0011] In conjunction with the first aspect, in some possible implementations, using the aforementioned ratio as the target color gain of the projection device in the aforementioned usage scenario includes: using the first ratio as the target color gain of the red channel of the projection device in the aforementioned usage scenario; using the second ratio as the target color gain of the green channel of the projection device in the aforementioned usage scenario; and using the third ratio as the target color gain of the blue channel of the projection device in the aforementioned usage scenario.

[0012] In conjunction with the first aspect, in some possible implementations, the aforementioned target ratio includes a first target ratio, a second target ratio, and a third target ratio; the aforementioned brightness compensation based on the aforementioned ratio to obtain the target ratio, and the use of the aforementioned target ratio as the target color gain of the projection device in the aforementioned usage scenario, includes: multiplying the aforementioned first ratio by a target coefficient to obtain the aforementioned first target ratio; multiplying the aforementioned second ratio by the aforementioned target coefficient to obtain the aforementioned second target ratio; multiplying the aforementioned third ratio by the aforementioned target coefficient to obtain the aforementioned third target ratio; wherein the aforementioned first target ratio, the aforementioned second target ratio, and the aforementioned third target ratio are all greater than or equal to 1; the aforementioned first target ratio is used as the target color gain of the projection device in the aforementioned usage scenario for the red channel; the aforementioned second target ratio is used as the target color gain of the projection device in the aforementioned usage scenario for the green channel; and the aforementioned third target ratio is used as the target color gain of the projection device in the aforementioned usage scenario for the blue channel.

[0013] In the above technical solution, since the first target ratio, the second target ratio, and the third target ratio are all greater than or equal to 1, the final determined target color gain for each color channel is greater than or equal to 1. This ensures that the image brightness after target color gain correction has minimal brightness loss compared to the image brightness before correction, which is beneficial for improving the user's visual experience. The image brightness before and after target color gain correction can be understood as the projection display brightness obtained by the projection device based on the target color gain correction.

[0014] In conjunction with the first aspect, in some possible implementations, the target coefficient is determined based on the following method: determining the minimum ratio among the first ratio, the second ratio, and the third ratio; and using the quotient obtained by dividing 1 by the minimum ratio as the target coefficient.

[0015] In the above technical solution, the quotient obtained by dividing 1 by the minimum ratio is used as the target coefficient, which is equivalent to normalization using the minimum ratio. This can maintain the relative gain ratio between each color channel, thus ensuring that the overall color balance is not destroyed, making the corrected color look more natural, avoiding color distortion caused by excessive color gain of a single color channel, and improving the accuracy of color correction.

[0016] In conjunction with the first aspect, in some possible implementations, the first color feature value includes: the average value of the first red chromaticity component and the average value of the first blue chromaticity component; the second color feature value includes: the average value of the second red chromaticity component and the average value of the second blue chromaticity component; the ratio includes: a fourth ratio between the average value of the first red chromaticity component and the average value of the second red chromaticity component, and a fifth ratio between the average value of the first blue chromaticity component and the average value of the second blue chromaticity component; determining the target color gain of the projection device in the above-mentioned usage scenario based on the above-mentioned ratio and luminance loss includes: if there is no luminance loss, taking the fourth ratio as the target color gain of the red chromaticity component of the projection device in the usage scenario, and taking the fifth ratio as the target color gain of the blue chromaticity component of the projection device in the usage scenario.

[0017] In conjunction with the first aspect, in some possible implementations, before determining the second color feature value of the optical-mechanical image region in the target image, the method further includes: determining the position coordinates of the optical-mechanical image region in a reference image; wherein the reference image is obtained by the camera after the projection device projects a preset feature image onto a third projection background; and the optical-mechanical image region in the target image is determined based on the position coordinates.

[0018] In conjunction with the first aspect, in some possible implementations, determining the position coordinates of the optical-mechanical screen area in the reference image includes: extracting a first feature point from the preset feature image; extracting a second feature point in the reference image corresponding to the first feature point; determining a projection transformation matrix based on the first feature point and the second feature point; determining the coordinates of the boundary points of the preset feature image based on the resolution of the projection device; and performing a projection transformation on the coordinates of the boundary points of the preset feature image based on the projection transformation matrix to obtain the position coordinates of the optical-mechanical screen area in the reference image.

[0019] In the above technical solution, high-precision alignment between the preset feature image and the reference image is achieved by matching corresponding feature points and determining the projection transformation matrix, thereby improving the accuracy of the determined optomechanical image area.

[0020] In conjunction with the first aspect, in some possible implementations, the projection device stores a calibration image in its memory. This calibration image is obtained by projecting a preset solid color image onto the first projection background using the projection device and then capturing it with the camera. The acquisition of the first color feature value includes:

[0021] Obtain the calibration image from the aforementioned memory; determine the first color feature value of the optical-mechanical image area in the aforementioned calibration image.

[0022] In conjunction with the first aspect, in some possible implementations, the first color feature value is stored in the memory of the projection device; obtaining the first color feature value includes: obtaining the first color feature value from the memory.

[0023] In the above technical solution, when using a projection device, there is no need to calculate the first color feature value; instead, the first color feature value is directly retrieved from memory. This improves the speed of determining the first color feature in the usage scenario, and consequently, the speed of determining the target color gain. Furthermore, directly storing the first color feature in memory also helps save storage space.

[0024] In conjunction with the first aspect, in some possible implementations, determining the second color feature value of the optical-mechanical image region in the target image includes: filtering candidate pixels in the optical-mechanical image region of the target image based on a dynamic threshold; wherein the dynamic threshold is determined based on the chromaticity components of each pixel in the optical-mechanical image region; the closeness between the color of each candidate pixel and the color of the preset pure color image is greater than a preset degree threshold; and determining the second color feature value based on each candidate pixel.

[0025] In the above technical solution, candidate pixels are selected in the optical-mechanical image area of ​​the target image by using dynamic thresholds. This can accurately find candidate pixels in complex backgrounds and then accurately find reference pixels, thereby improving the color adaptation effect. It has high flexibility and accuracy.

[0026] In conjunction with the first aspect, in some possible implementations, determining the second color feature value based on each candidate pixel includes: determining the brightness value of each candidate pixel, and sorting the candidate pixels in descending order of brightness value to obtain a sorting result; selecting candidate pixels that are in the top preset percentage as reference pixels based on the sorting result; and determining the second color feature value based on each reference pixel.

[0027] In the above technical solution, it is considered that noise in an image typically causes random fluctuations in pixel values. This noise effect is more significant in low-brightness areas because the signal strength and signal-to-noise ratio are lower in these areas. In contrast, high-brightness areas have higher signal strength and a higher signal-to-noise ratio, and are therefore less affected by noise. Therefore, the accuracy of the second color feature value determined based on reference pixels with higher brightness values ​​is higher. Furthermore, high-brightness areas exhibit better color consistency; color variations are typically smaller and more uniform under different background and lighting conditions, making the second color feature value determined based on reference pixels with higher brightness values ​​more reliable.

[0028] In conjunction with the first aspect, in some possible implementations, determining the second color feature value based on each of the reference pixels includes: averaging the red channel values ​​of each of the reference pixels to obtain a second red channel average value in the second color feature value; averaging the green channel values ​​of each of the reference pixels to obtain a second green channel average value in the second color feature value; averaging the blue channel values ​​of each of the reference pixels to obtain a second blue channel average value in the second color feature value; or, averaging the red chromaticity component values ​​of each of the reference pixels to obtain a second red chromaticity component average value in the second color feature value; averaging the blue chromaticity component values ​​of each of the reference pixels to obtain a second blue chromaticity component average value in the second color feature value.

[0029] In conjunction with the first aspect, in some possible implementations, the aforementioned dynamic threshold includes: a dynamic threshold corresponding to the red chromaticity component in the target image and a dynamic threshold corresponding to the blue chromaticity component in the target image; the dynamic threshold corresponding to the red chromaticity component in the target image is determined based on the red chromaticity component of each pixel in the optical-mechanical image region of the target image; the dynamic threshold corresponding to the blue chromaticity component in the target image is determined based on the blue chromaticity component of each pixel in the optical-mechanical image region of the target image.

[0030] In conjunction with the first aspect, in some possible implementations, the dynamic thresholds corresponding to the red chromaticity component and the blue chromaticity component in the target image are determined as follows: the optical-mechanical image area of ​​the target image is divided into multiple sub-regions; the mean of the red chromaticity component and the mean of the blue chromaticity component in each sub-region are calculated; the standard deviation of the red chromaticity component and the standard deviation of the blue chromaticity component in each sub-region are calculated; sub-regions that meet preset screening conditions are selected from the multiple sub-regions as target sub-regions; wherein, the standard deviation of the red chromaticity component in the target sub-region is greater than or equal to a first preset threshold, and The standard deviation of the blue chromaticity component of the aforementioned target sub-region is greater than or equal to a second preset threshold; the average of the mean values ​​of the red chromaticity components of all target sub-regions is used to obtain a first mean, and the average of the mean values ​​of the blue chromaticity components of all target sub-regions is used to obtain a second mean; the average of the standard deviations of the red chromaticity components of all target sub-regions is used to obtain a third mean, and the average of the standard deviations of the blue chromaticity components of all target sub-regions is used to obtain a fourth mean; based on the first mean and the third mean, the dynamic threshold corresponding to the aforementioned red chromaticity component is determined; based on the second mean and the fourth mean, the dynamic threshold corresponding to the aforementioned blue chromaticity component is determined.

[0031] In conjunction with the first aspect, in some possible implementations, the aforementioned preset solid color image is a pure white image, and the aforementioned first projection background is a pure white projection background.

[0032] In the above technical solution, since pure white is the brightest color and contains the full spectrum, using pure white is beneficial for achieving maximum brightness levels and white balance settings. Furthermore, pure white is simple and intuitive, and easily measured and described accurately, for example, using RGB values ​​(255, 255, 255). This makes color feature value difference analysis more direct and reduces the complexity introduced by other colors.

[0033] Secondly, a projection control device is provided for use in a projection device, wherein the projection device has a built-in camera, and the projection control device includes: a first acquisition module for acquiring a first color feature value; wherein the first color feature value is obtained by the projection device projecting a preset solid color image onto a first projection background; and the first projection background is located in a calibration scene of the projection device.

[0034] A determining module is used to determine a second color feature value of the optical-mechanical image area in the target image; wherein the target image is obtained by the camera after the preset pure color image is projected onto the second projection background by the projection device; the second projection background is located in the usage scenario of the projection device; a second acquiring module is used to acquire a ratio based on the first color feature value and the second color feature value; a color gain determining module is used to determine the target color gain of the projection device in the usage scenario based on the ratio and brightness loss; wherein the brightness loss is determined based on the ratio or based on the projection display brightness of the projection device, and the projection display brightness is the display brightness of any image to be projected onto the second projection background by the projection device.

[0035] Thirdly, a projection device is provided, comprising: a memory for storing executable program code; and a processor for calling and running the executable program code from the memory, causing the projection device to perform the method of the first aspect or any possible implementation thereof.

[0036] Fourthly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof.

[0037] Fifthly, a computer-readable storage medium is provided that stores computer program code, which, when executed on a computer, causes the computer to perform the methods described in the first aspect or any possible implementation thereof. Attached Figure Description

[0038] Figure 1 is a schematic flowchart of a projection control method provided in an embodiment of this application;

[0039] Figure 2 is a schematic diagram of the optomechanical screen area in a calibration image provided in an embodiment of this application;

[0040] Figure 3 is a schematic diagram of a chessboard image provided in an embodiment of this application;

[0041] Figure 4 is a schematic diagram of a dot image provided in an embodiment of this application;

[0042] Figure 5 is a schematic diagram of a checkerboard image, a reference image, and an optical-mechanical screen area in the reference image provided in an embodiment of this application.

[0043] Figure 6 is a schematic flowchart of another projection control method provided in an embodiment of this application;

[0044] Figure 7 is a schematic diagram of a projection control device provided in an embodiment of this application;

[0045] Figure 8 is a schematic diagram of the structure of a projection device provided in an embodiment of this application. Detailed Implementation

[0046] The technical solutions in this application will be clearly and thoroughly described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in the text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0047] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature.

[0048] Projection devices project images or videos onto a wall or screen, allowing users to view the projected image. In practical applications, projectors often face diverse projection backgrounds, such as ordinary walls, standard screens, and walls with varying color differences. These non-white backgrounds often result in color discrepancies in the projected image, severely impacting the user's viewing experience.

[0049] To improve the user viewing experience, many projector manufacturers have incorporated manual color temperature adjustment into their devices. Users can adjust the color temperature to reduce color difference and improve color reproduction. However, the inventors of this application have discovered the following problems: First, manually adjusting the color temperature requires a certain level of expertise, which may be challenging for ordinary users. Second, even with color temperature adjustment, color reproduction remains poor due to differences in wall materials, colors, and other factors. Therefore, how to improve color reproduction while avoiding manual adjustment by the user has become a pressing technical problem.

[0050] In related technologies, to avoid manual adjustments by users, some projectors are beginning to incorporate adaptive background color functionality. This adaptive function uses a built-in camera and color analysis algorithms to automatically detect the color of the projected background. Based on a mapping table calibrated at the projector's factory between different background colors and calibration parameters, it looks up the corresponding calibration parameters for the currently detected background color. Based on these calibration parameters, it adjusts the projector's color parameters to achieve automated color reproduction. These calibration parameters may include color gain, color temperature, and other parameters.

[0051] However, the inventors of this application have discovered that the above-mentioned adaptive function has the following two problems:

[0052] Firstly, inconsistent results: Projectors of different brands and models exhibit significant differences in their background color adaptation performance. Some devices may over-adjust or under-adjust, resulting in poor color reproduction. The reasons for this poor color reproduction in the aforementioned adaptive function include:

[0053] 1.1 Limited Color Samples: The calibration of the mapping table may only cover a limited number of background color samples. In real-world environments, a wider variety of background colors may appear, and these uncalibrated background colors are difficult to accurately correct using existing mapping tables. Furthermore, continuously adding background color samples will significantly increase the calibration workload and affect calibration efficiency.

[0054] 1.2 Inconsistent Lighting Conditions: The lighting conditions during calibration (such as light source type, intensity, and direction) may differ from those in the actual usage environment. Changes in lighting conditions can affect the perception and measurement of background color, leading to inaccurate adjustments to the calibration mapping table in the actual usage environment, and consequently affecting color reproduction.

[0055] 1.3 Complexity of Color Spaces: Color spaces are multidimensional, meaning they typically have multiple dimensions (such as the three dimensions of RGB), which increases the complexity of mapping. High-dimensional color spaces require more data points to accurately describe the relationships between colors, while limited calibration samples may not be sufficient to cover all colors. This makes it difficult for pre-calibrated mapping tables to cover various usage scenarios in real-world environments.

[0056] 1.4 Static nature of mapping tables: Mapping tables are usually static. They are calibrated before the projector leaves the factory and stored in the projector's memory. Static mapping tables may not be able to adapt to environmental changes in real time, have poor flexibility, and result in poor calibration effects in certain environments.

[0057] Secondly, regarding brightness loss: The aforementioned adaptive function defaults to obtaining correction parameters based on a mapping table, and after adjusting the projector's color parameters using these parameters, there is no brightness loss. However, the inventors of this application have discovered that, in reality, even after directly adjusting the projector's color parameters using these correction parameters, brightness loss may still occur. In other words, when adjusting the projector using the aforementioned adaptive function to achieve better color reproduction, brightness loss may sometimes accompany the process. This brightness loss can lead to reduced image visibility, weakened color performance, and decreased viewing comfort, resulting in a poor user experience.

[0058] Based on this, in order to automatically improve color reproduction while avoiding or reducing brightness loss, this application provides a projection control method applied to a projection device. By comparing color feature values ​​in a calibration scene and the usage scene, rather than relying on a pre-calibrated mapping table, color gain can be adjusted more accurately. Furthermore, when adjusting color gain, brightness loss is considered and brightness compensation is performed to avoid or reduce brightness loss caused by color gain adjustment. Simultaneously, the entire adjustment process is completed automatically, requiring no manual adjustment by the user, thus improving the user experience. Therefore, by comparing color feature values ​​in the calibration scene and the usage scene, and combining this with a brightness compensation mechanism, it is possible to automatically improve color reproduction while reducing or avoiding brightness loss.

[0059] The projection device in this embodiment has a built-in camera, which can be understood as a projector that integrates one or more cameras. These cameras can be used for various purposes, such as autofocus, keystone correction, color management, and interactive functions. The built-in camera enables the projector to automatically adjust settings to optimize image quality without manual user intervention, providing a hardware foundation for automatically improving color reproduction.

[0060] Figure 1 is a schematic flowchart of a projection control method provided in an embodiment of this application.

[0061] For example, as shown in Figure 1, the projection control method includes:

[0062] Step 101: Obtain the first color feature value; wherein, the first color feature value is obtained by projecting a preset solid color image onto the first projection background through the projection device; the first projection background is located in the calibration scene of the projection device.

[0063] Step 102: Determine the second color feature value of the optical-mechanical screen area in the target image; wherein, the target image is obtained by using a camera after the preset pure color image is projected onto the second projection background by a projection device; the second projection background is located in the usage scenario of the projection device.

[0064] Step 103: Obtain the ratio based on the first color feature value and the second color feature value.

[0065] Step 104: Based on the above ratio and brightness loss, determine the target color gain of the projection device in the usage scenario; wherein, the brightness loss is determined based on the ratio or based on the projection display brightness of the projection device, and the projection display brightness is the display brightness of any image to be projected onto the second projection background.

[0066] In the embodiment shown in Figure 1, the first color feature value is obtained by projecting a preset pure color image onto a first projection background through a projection device in a calibration scene. In the calibration scene, environmental conditions (such as lighting, background color, and temperature) are strictly controlled and standardized to ensure the consistency and accuracy of the calibration process. Therefore, the first color feature value obtained in the calibration scene is highly reliable and can serve as a precise reference for subsequent comparisons. The second color feature value is obtained by projecting a preset pure color image onto a second projection background through a projection device in the usage scene. This ensures that the same preset pure color image is used for projection in both the usage and calibration scenes, guaranteeing that the only variable between the two projections in the calibration and usage scenes is the change in the projection background. Extracting the second color feature value from the optical engine screen area of ​​the target image can accurately filter out the influence of non-optical engine screen areas, allowing the determined second color feature value to accurately reflect the color effect output by the projection device in the usage scene. The ratio obtained based on the first and second color feature values ​​can characterize the color difference between images captured by the camera built into the projection device in the calibration and usage scenes, providing accurate data reference for obtaining the target color gain. Based on the ratio and luminance loss, the target color gain of the projection device in the usage scenario is determined. Luminance loss is taken into account when determining the target color gain, which helps to reduce or avoid potential luminance loss in the image after adjustment with this target color gain. Therefore, it achieves automatic improvement in color reproduction while reducing or avoiding luminance loss.

[0067] The specific implementation of each step in the embodiment shown in Figure 1 is described below:

[0068] In step 101, the first color feature value can be the color feature value of the calibration image. This calibration image is obtained by projecting a preset pure color image onto a first projection background in the calibration scene using a projection device, and then capturing the image using the camera built into the projection device. For example, the color feature value of the optical-mechanical image area in the calibration image can be used as the aforementioned first color feature value. This first color feature value can be a color feature value in a target color space, such as RGB, YUV, etc. The first color feature value can be understood as the average color value of the pixels in the optical-mechanical image area of ​​the calibration image. For example, the average color value of the pixels in the optical-mechanical image area of ​​the calibration image can be the average color value of the pixels in the optical-mechanical image area of ​​the calibration image in the RGB color space, or the average color value of the pixels in the optical-mechanical image area of ​​the calibration image in the YUV color space.

[0069] In a calibration scenario, environmental conditions (such as lighting, background color, and temperature) are strictly controlled and standardized to ensure the consistency and accuracy of the calibration process. This calibration scenario is used to calibrate and adjust projection equipment before it leaves the factory. Typically, projection equipment manufacturers test various performance indicators (including but not limited to color accuracy and brightness uniformity) of the projection equipment in a controlled calibration environment and make corresponding adjustments or settings as needed to ensure that the projection equipment can function normally according to design specifications.

[0070] The first projection background is the projection background in the calibration scene. This projection background can be a screen, wall, or other background suitable for projection. The background color of this projection background can be set according to actual needs. Similarly, the specific color of the preset solid color image can also be set according to actual needs. The color of the preset solid color image can be the same as the background color of the first projection background.

[0071] In one possible implementation, the preset solid color image is a pure white image, and the first projection background is a pure white projection background. That is, both the preset solid color image and the first projection background are pure white.

[0072] Since pure white is the brightest color and contains the full spectrum, using pure white is beneficial for achieving maximum brightness levels and white balance settings. Pure white is simple and intuitive, and is easy to measure and describe accurately, for example, through RGB values ​​(255, 255, 255). This makes color feature value difference analysis more direct and reduces the complexity introduced by other colors.

[0073] In one possible implementation, the calibration image is taken under the premise that the white balance has been calibrated by the camera built into the projection device. This helps to ensure that the color of the calibration image taken by the camera built into the projection device is close to the real effect, thereby further improving the reliability of the first color feature value extracted from the calibration image.

[0074] In one possible implementation, the projection device stores a calibration image in its memory. This calibration image is obtained by projecting a preset solid color image onto a first projection background and then capturing it using the camera built into the projection device. The aforementioned acquisition of the first color feature value includes: acquiring the calibration image from memory; and determining the first color feature value of the optical-mechanical image area within the calibration image.

[0075] Specifically, before the projection device leaves the factory, a calibration image captured by the projector's built-in camera can be stored in the projector's memory. Therefore, when the color gain of the projector needs to be adjusted in a usage scenario, the calibration image can be retrieved from the projector's memory, and the first color feature value of the optical-mechanical image area in the calibration image can be determined. In this implementation, it is not necessary to determine the first color feature value before the projector leaves the factory; instead, the calibration image is retrieved from the projector's memory and the first color feature value is determined only after the projector has left the factory and is applied to the actual usage scenario.

[0076] The optical-mechanical image, generally speaking, refers to the image generated and projected onto the projection background by the light source and optical system of the projection device. The optical-mechanical image is also the optical-mechanical image projected by the projection device, which refers to the image generated and projected by the internal optical system of the projection device. In the embodiments of this application, the optical-mechanical image area in the calibration image refers to the area in the calibration image where the preset solid color image projected by the projection device onto the first projection background is located; it can also be understood as the effective area of ​​the preset solid color image in the calibration image. For example, referring to Figure 2, the optical-mechanical image area 202 in the calibration image 201 is the area where the preset solid color image is located in the calibration image 201, which is the area within the dashed box in Figure 2.

[0077] In another possible implementation, the projection device stores a first color feature value in its memory; the above-mentioned acquisition of the first color feature value includes: acquiring the first color feature value from memory.

[0078] Specifically, before the projection device leaves the factory, a first color feature value for the optical-mechanical image region in the calibration image can be determined based on the calibration image captured in the calibration scene, and this first color feature value is stored in the projection device's memory. Therefore, after the projection device leaves the factory, in the usage scenario, it is not necessary to recalculate the first color feature value; instead, it is directly retrieved from memory. This improves the speed of determining the first color feature in the usage scenario, and consequently, the speed of determining the target color gain in the usage scenario. Furthermore, directly storing the first color feature in memory also helps save storage space.

[0079] In step 102, after projecting a preset solid color image onto the second projection background in the usage scenario using a projection device, the image captured by the camera is used as the target image. Then, the second color feature value of the optical-mechanical image region in the target image is determined. This second color feature value is a color feature value in the target color space, and the second color feature value and the first color feature value belong to the same color space. For ease of description, in this embodiment, the color feature value of the optical-mechanical image region in the target image is referred to as the second color feature value, and the color feature value of the optical-mechanical image region in the calibration image is referred to as the first color feature value. The second color feature value can be understood as: the average color value of the pixels in the optical-mechanical image region of the target image. For example, the average color value of the pixels in the optical-mechanical image region of the target image can be: the average color value of the pixels in the optical-mechanical image region of the target image in the RGB color space, or: the average color value of the pixels in the optical-mechanical image region of the target image in the YUV color space.

[0080] The usage scenario refers to the actual usage scenario in which the projection device is used by the user after it leaves the factory. This usage scenario may be an indoor scenario or an outdoor scenario.

[0081] The second projection background is the background for the usage scenario, and it can be the background on which the user expects the projected image to be projected. When the user uses the projection device indoors, the second projection background may be a wall or a screen in the indoor scene. When the user uses the projection device outdoors, the second projection background may be a wall or a screen in the outdoor scene. The preset solid color image projected on the second projection background is the same solid color image as the preset solid color image projected on the first projection background. Since the second projection background is the projection background for the user's usage scenario, the user can choose it according to actual needs; therefore, in specific implementations, the background color of the second projection background may be any color.

[0082] The optical-mechanical image area in the target image refers to the area in the target image where the preset solid color image projected by the projection device onto the second projection background is located. It can also be understood as the effective area of ​​the preset solid color image in the target image.

[0083] For a known projection device, the position coordinates of the optical-mechanical image area in each image captured by the built-in camera are usually fixed. Based on this, in the embodiments of this application, the position coordinates can be predetermined, and then the optical-mechanical image area in the target image can be determined according to the position coordinates. Correspondingly, the optical-mechanical image area in the calibration image can also be determined according to the position coordinates.

[0084] In some embodiments, the process of determining the optical-mechanical image region in the target image is performed before determining the second color feature value of the optical-mechanical image region in the target image. For example, the method of determining the optical-mechanical image region in the target image may include the following steps S11 to S12:

[0085] S11: Determine the position coordinates of the optical-mechanical screen area in the reference image.

[0086] The reference image is obtained by projecting a preset feature image onto a third projection background using the camera built into the projection device.

[0087] The third projection background can be located in the calibration scene, and the third projection background and the first projection background mentioned above can be the same projection background or different projection backgrounds. This application embodiment does not make specific limitations in this regard.

[0088] The preset feature image is an image with feature points, and these feature points are prominent and easily identifiable. For example, the preset feature image can be a pattern image, which can be a checkerboard image as shown in Figure 3, or a dot image as shown in Figure 4. This application embodiment does not specifically limit the size of the preset feature image; for example, it does not limit the length and width of the checkerboard image and the dot image.

[0089] For example, referring to Figure 5, the image on the left in Figure 5 is a checkerboard image projected onto the third projection background by a projection device. This checkerboard image can be understood as the original optical-mechanical image, or simply the optical-mechanical image. The image on the right in Figure 5 is a reference image obtained by using the camera built into the projection device after the checkerboard image is projected onto the third projection background. The optical-mechanical image area in this reference image is the area enclosed by the four points x1', x2', x3', and x4' in the figure. There is a one-to-one mapping relationship between the four points x1', x2', x3', and x4' in Figure 5. It is understandable that since the checkerboard image is a known image, the position coordinates of the four points x1', x2', x3', and x4' are essentially known. Therefore, if the mapping relationship between the checkerboard image and the reference image in Figure 5 is known, then the position coordinates of the four points x1', x2', x3', and x4' can be obtained based on this mapping relationship and the position coordinates of x1', x2', x3', and x4'. These position coordinates can then be used as the position coordinates of the optical-mechanical image area. This mapping relationship can be specifically represented as the projection transformation matrix between the checkerboard image and the reference image, also known as the homography matrix, or simply the H matrix.

[0090] For example, the position coordinates of the optical-mechanical screen area in the reference image can also be stored in the memory of the projection device. Thus, when it is necessary to determine the optical-mechanical screen area in the target image in the usage scenario, the position coordinates can be obtained from the memory, and the optical-mechanical screen area in the target image can be determined based on the position coordinates.

[0091] S12: Determine the optical-mechanical image area in the target image based on the above position coordinates.

[0092] It is understandable that the images captured by the built-in camera of the projection device should be of the same size. Assuming that the target image and the aforementioned reference image have the same size, the position coordinates of the optical-mechanical screen area in the target image should be the same as those in the reference image. Assuming these position coordinates are the coordinates of the four points x1', x2', x3', and x4' mentioned above, then the area enclosed by the position coordinates of these four points in the target image can be considered as the optical-mechanical screen area in the target image.

[0093] Since the calibration image is essentially an image captured by the camera built into the projection device, a similar method can be used to determine the optical-mechanical image area in the calibration image based on the aforementioned position coordinates. For example, the area enclosed by the position coordinates of the four points x1', x2', x3', and x4' in the calibration image can be taken as the optical-mechanical image area in the calibration image.

[0094] In one possible implementation, determining the position coordinates of the optical-mechanical image area in the reference image includes the following steps S111 to S115:

[0095] S111: Extract the first feature point from the preset feature image.

[0096] The first feature point can be a representative feature point extracted from a preset feature image. These feature points can be corners, edges, or other points with unique attributes, and they must be stable and repeatable points within the preset feature image. A preset feature point detection algorithm can be used to extract the first feature point from the preset feature image and calculate its position coordinates. Commonly used feature point detection algorithms include SIFT (Scale-Invariant Feature Transform), SURF (Speeded-Up Robust Features), and ORB (Oriented FAST and Rotated BRIEF). This application does not specifically limit the feature point detection algorithm used.

[0097] For example, if the preset feature image is a chessboard image projected by a projection device, then the corner points of the chessboard image can be extracted and denoted as corner point 1. Corner point 1 is the first feature point.

[0098] S112: Extract the second feature point in the reference image that corresponds to the first feature point.

[0099] Specifically, a point in the reference image that matches the first feature point can be used as the second feature point. A pre-defined feature matching algorithm can typically extract the second feature point matching the first feature point from the reference image. Examples of pre-defined feature matching algorithms include brute-force matching and the FLANN matcher (Fast Library for Approximate Nearest Neighbors), but this application does not specifically limit the specific algorithm used.

[0100] For example, if the preset feature image is a checkerboard image, then corner point 2 that matches corner point 1 above can be extracted from the reference image. This corner point 2 is the second feature point.

[0101] S113: Determine the projection transformation matrix based on the first feature point and the second feature point.

[0102] Since the first and second feature points are matching feature point pairs, these matching feature point pairs can be used to calculate the projection transformation matrix. This projection transformation matrix describes the geometric transformation relationship between the preset feature image and the reference image.

[0103] For example, based on the one-to-one correspondence between corner point 1 and corner point 2, the projection transformation matrix, i.e. the H matrix, can be obtained. The H matrix can be used to transform the pixels on the preset feature image onto the reference image (e.g., X_2 = H*X_1, where X_1 represents the position coordinates of the pixel on the preset feature image and X_2 represents the position coordinates of the pixel on the reference image).

[0104] S114: Determine the coordinates of the boundary points of the preset feature image based on the resolution of the projection device.

[0105] The boundary points of the preset feature image can include the four vertices of the preset feature image, which can be understood as the four vertices of the optical engine screen of the projection device. The pixel coordinates of these boundary points can be directly obtained based on the resolution of the projection device. Referring to Figure 5, assuming the resolution of the projection device is 1080P, the coordinates of the boundary points of the preset feature image projected by the projection device include: x1(0,0), x2(1920,0), x3(1920,1080), x4(0,1080).

[0106] S115: Based on the projection transformation matrix, perform projection transformation on the coordinates of the boundary points of the preset feature image to obtain the position coordinates of the optical-mechanical screen area in the reference image.

[0107] For example, the coordinates x1', x2', x3', x4' of the four vertices of the optical-mechanical image area in the reference image can be obtained through the H matrix (e.g., x1' = H*x1, x2' = H*x2, x3' = H*x3, x4' = H*x4).

[0108] In this embodiment, high-precision alignment between the preset feature image and the reference image is achieved by matching corresponding feature points and determining the projection transformation matrix, thereby improving the accuracy of the determined optomechanical image area.

[0109] In one possible implementation, the method for determining the second color feature value of the optical-mechanical image region in the target image includes the following steps S21 to S22:

[0110] S21: Based on a dynamic threshold, select candidate pixels in the optical-mechanical image region of the target image.

[0111] The dynamic threshold is determined based on the chromaticity components of pixels in the optical-mechanical image region of the target image. The similarity between the color of each candidate pixel and the color of a preset pure color image is greater than a preset threshold.

[0112] Specifically, the chromaticity components of a pixel can include the red chromaticity component Cr and the blue chromaticity component Cb in the YUV color space. A preset threshold can be pre-defined, where the proximity between the color of a candidate pixel and the color of a preset pure color image is greater than the preset threshold, indicating that the color of the candidate pixel is the same as or very close to the color of the preset pure color image.

[0113] For example, if the preset solid color image is pure white, then based on a dynamic threshold, candidate pixels located in the near-white region are selected from the optical and mechanical image area of ​​the target image; that is, all candidate pixels located in the near-white region are selected. The near-white region refers to the pixel area in the optical and mechanical image area of ​​the target image whose color is close to pure white. Since all candidate pixels in the near-white region belong to the near-pure white area, these candidate pixels can be called candidate white points. If the preset solid color image is pure blue, then based on a dynamic threshold, candidate pixels located in the near-blue region are selected from the optical and mechanical image area of ​​the target image. The near-blue region refers to the pixel area in the optical and mechanical image area of ​​the target image whose color is close to pure blue. Since all candidate pixels in the near-blue region belong to the near-pure blue area, these candidate pixels can be called candidate blue points. It should be noted that this embodiment only uses the preset solid color image being pure white or pure blue as an example. In specific implementations, if the preset solid color image is another color, a similar method can be used to select candidate pixels.

[0114] In one possible implementation, the aforementioned dynamic thresholds include: a dynamic threshold corresponding to the red chromaticity component and a dynamic threshold corresponding to the blue chromaticity component in the target image; the dynamic threshold corresponding to the red chromaticity component in the target image is determined based on the red chromaticity component of each pixel in the optical-mechanical image region of the target image; the dynamic threshold corresponding to the blue chromaticity component in the target image is determined based on the blue chromaticity component of each pixel in the optical-mechanical image region of the target image. That is, the dynamic threshold corresponding to the red chromaticity component in the target image is determined based on the red chromaticity component of all pixels in the optical-mechanical image region of the target image. The dynamic threshold corresponding to the blue chromaticity component in the target image is determined based on the blue chromaticity component of all pixels in the optical-mechanical image region of the target image.

[0115] Based on the dynamic thresholds corresponding to the red and blue chromaticity components in the target image, candidate pixels are selected in the optical-mechanical image region of the target image. The red chromaticity components of the candidate pixels all satisfy the dynamic thresholds corresponding to the red chromaticity components, and the blue chromaticity components of the candidate pixels all satisfy the dynamic thresholds corresponding to the blue chromaticity components. This is beneficial for accurately selecting all candidate pixels in the optical-mechanical image region of the target image from different chromaticity components.

[0116] In one possible implementation, the determination of the dynamic threshold corresponding to the red chromaticity component and the dynamic threshold corresponding to the blue chromaticity component in the target image includes the following steps S31 to S38:

[0117] S31: Divide the optical-mechanical image area of ​​the target image into multiple sub-regions.

[0118] Specifically, based on the position coordinates of the optical-mechanical image area determined above, the area within the four points x1', x2', x3', and x4' of the target image can be considered as the optical-mechanical image area, and this area can be divided into multiple sub-regions. These multiple sub-regions can be obtained by dividing the optical-mechanical image area of ​​the target image on an average basis, that is, each sub-region can be the same size. In this embodiment, the number of sub-regions is not specifically limited; optionally, the optical-mechanical image area of ​​the target image can be divided into 12 sub-regions.

[0119] Considering that the target image is an image captured by the camera built into the projection device, and that the image captured by the camera is in RGB format, and as mentioned above, the dynamic threshold is determined based on the chromaticity components, which are characteristic values ​​of the YUV format. Therefore, in step S31 above, the RGB format target image can first be converted to a YUV format target image, and then the optical-mechanical image area of ​​the YUV format target image can be divided into multiple sub-regions.

[0120] S32: Calculate the mean of the red chromaticity component and the mean of the blue chromaticity component for each sub-region.

[0121] As can be understood from the above, the multiple sub-regions are obtained by dividing the optical and mechanical image area of ​​the YUV format target image. Therefore, each pixel in each sub-region has a red chromaticity component Cr and a blue chromaticity component Cb. Thus, for each sub-region, the mean value M1 of the red chromaticity component and the mean value M2 of the blue chromaticity component of that sub-region can be calculated based on the red chromaticity component Cr and the blue chromaticity component Cb of each pixel in that sub-region.

[0122] For example, for each sub-region, M1 and M2 can be calculated using the following formula:

[0123] Where (i,j) represents the pixel coordinates within the sub-region, N is the number of pixels within the sub-region, and C r (i,j) represents the red chromaticity component of the pixel with pixel coordinates (i,j), C b (i,j) represents the blue chromaticity component of the pixel with pixel coordinates (i,j).

[0124] S33: Calculate the standard deviation of the red chromaticity component and the standard deviation of the blue chromaticity component for each sub-region.

[0125] Specifically, for each sub-region, the standard deviation D1 of the red chromaticity component and the standard deviation D2 of the blue chromaticity component of the sub-region can be calculated based on the red chromaticity component Cr and the blue chromaticity component Cb of each pixel in the sub-region.

[0126] For example, for each sub-region, D1 and D2 can be calculated using the following formula:

[0127] S34: Select the sub-regions that meet the preset filtering conditions from multiple sub-regions as the target sub-regions.

[0128] Specifically, the standard deviation D1 of the red chromaticity component of the target sub-region is greater than or equal to a first preset threshold, and the standard deviation D2 of the blue chromaticity component of the target sub-region is greater than or equal to a second preset threshold. These first and second preset thresholds can be pre-calibrated and can be empirical values ​​set manually based on multiple experimental results.

[0129] S35: Average the red chromaticity components of all target sub-regions to obtain the first average, and average the blue chromaticity components of all target sub-regions to obtain the second average.

[0130] It is understandable that in S32 above, the mean value M1 of the red chromaticity component and the mean value M2 of the blue chromaticity component of each sub-region are calculated. Therefore, each target sub-region has its own mean value M1 of the red chromaticity component. Based on this, the mean values ​​M1 of the red chromaticity components of all target sub-regions selected in S34 can be further averaged to obtain a first mean value of the red chromaticity component representing the target image, denoted as Mr. Similarly, each target sub-region has its own mean value M2 of the blue chromaticity component. Based on this, the mean values ​​M2 of the blue chromaticity components of all target sub-regions selected in S34 can be further averaged to obtain a second mean value of the blue chromaticity component representing the target image, denoted as Mb.

[0131] S36: Average the standard deviations of the red chromaticity components of all target sub-regions to obtain the third mean, and average the standard deviations of the blue chromaticity components of all target sub-regions to obtain the fourth mean.

[0132] It is understandable that in S33 above, the standard deviation D1 of the red chromaticity component and the standard deviation D2 of the blue chromaticity component of each sub-region are calculated. Therefore, each target sub-region has its own standard deviation D1 of the red chromaticity component. Based on this, the standard deviations D1 of the red chromaticity components of all target sub-regions selected in S34 can be further averaged to obtain a third mean of the standard deviations of the red chromaticity components representing the target image, denoted as Dr. Similarly, each target sub-region has its own standard deviation D2 of the blue chromaticity component. Based on this, the standard deviations D2 of the blue chromaticity components of all target sub-regions selected in S34 can be further averaged to obtain a fourth mean of the standard deviations of the blue chromaticity components representing the target image, denoted as Db.

[0133] S37: Determine the dynamic threshold corresponding to the red chromaticity component in the target image based on the first mean and the third mean.

[0134] Specifically, based on the first mean Mr and the third mean Dr, the dynamic threshold corresponding to the red chromaticity component in the target image can be: (k*Mr+Dr*sign(Mr))±k*Dr.

[0135] Where k is a constant, which can be set according to actual needs. In this embodiment, k can be set to 1.5. When Mr is less than 0, sign(Mr) = -1; when Mr is greater than 0, sign(Mr) = 1; when Mr is equal to 0, sign(Mr) = 0.

[0136] S38: Determine the dynamic threshold corresponding to the blue chromaticity component in the target image based on the second mean and the fourth mean.

[0137] Specifically, based on the second mean Mb and the fourth mean Db, the dynamic threshold corresponding to the blue chromaticity component in the target image can be: (Mb+Db*sign(Mb))±k*Db.

[0138] Where k is a constant, which can be set according to actual needs. In this embodiment, k can be set to 1.5. When Mb is less than 0, sign(Mb) = -1; when Mb is greater than 0, sign(Mb) = 1; when Mb is equal to 0, sign(Mb) = 0.

[0139] After obtaining the dynamic thresholds corresponding to the red and blue chromaticity components in the target image, the specific method for filtering all candidate pixels in the optical-mechanical image region of the target image based on the dynamic thresholds can be as follows: All candidate pixels are filtered in the optical-mechanical image region of the target image using the following formulas 1 and 2: (k*Mr+Dr*sign(Mr))-k*Dr<C r (i,j)<(k*Mr+Dr*sign(Mr))+k*Dr Formula 1 (Mb+Db*sign(Mb))-k*Db<C b (i,j)<(Mb+Db*sign(Mb))+k*Db Formula 2

[0140] Formula 1 can be simplified to Formula 3, and Formula 2 can be simplified to Formula 4: |C r (i,j)-(k*Mr+Dr*sign(Mr))|<k*Dr Formula 3 |C b (i,j)-(Mb+Db*sign(Mb))|<k*Db Formula 4

[0141] For each pixel in the optical-mechanical image region of the target image, the red chromaticity component C of that pixel is... r Substituting (i,j) into Formula 3 above, we determine the red chromaticity component C. r Can (i,j) satisfy the inequality in Formula 3, and what is the blue chromaticity component C of this pixel? b Substituting (i,j) into Formula 4 above, we determine the blue chromaticity component C. b Does (i,j) satisfy the inequality in Formula 4? If the red chromaticity component C of this pixel... r (i,j) satisfies the inequality in Formula 3, and the blue chromaticity component C b If pixel (i,j) satisfies the inequality in Formula 4, then that pixel is identified as a candidate pixel. Based on this method, all pixels satisfying Formulas 3 and 4 can be selected as candidate pixels from the optical-mechanical image region of the target image.

[0142] In this embodiment, candidate pixels are selected in the optical-mechanical image area of ​​the target image by using a dynamic threshold. This can accurately find each candidate pixel in a complex background, and then accurately find each reference pixel, thereby improving the color adaptation effect. It has both high flexibility and accuracy.

[0143] It should be noted that the above example uses a dynamic threshold to filter candidate pixels in the optical-mechanical image region of the target image. In a practical implementation, a static threshold can also be used to filter candidate pixels in the optical-mechanical image region of the target image. For example, assuming the color of a solid color image is pure white, the RGB value corresponding to pure white is (255, 255, 255). Based on this, the static threshold can be set to 240. If a pixel in the optical-mechanical image region has channel values ​​greater than 240 in all three RGB color channels, it can be determined that the pixel belongs to the candidate pixel in the near-white region.

[0144] S22: Determine the second color feature value based on each candidate pixel.

[0145] In one possible implementation, when the second color feature value is a color feature value in the RGB color space, it can be determined based on the red channel values ​​(R value), green channel values ​​(G value), and blue channel values ​​(B value) of all candidate pixels. Specifically, the second color feature value can include: the second color feature value of the red channel calculated based on the R values ​​of all candidate pixels, the second color feature value of the green channel calculated based on the G values ​​of all candidate pixels, and the second color feature value of the blue channel calculated based on the B values ​​of all candidate pixels. Correspondingly, a similar method can be used to obtain the first color feature value for the calibration image, which can specifically include: the first color feature value of the red channel, the first color feature value of the green channel, and the first color feature value of the blue channel.

[0146] In another possible implementation, when the second color feature value is a color feature value in the YUV color space, it can be determined based on the red chromaticity component (Cr value) and blue chromaticity component (Cb value) of each candidate pixel. This second color feature value can specifically include: a second color feature value for the red chromaticity component calculated based on the Cr values ​​of all candidate pixels, and a second color feature value for the blue chromaticity component calculated based on the Cb values ​​of all candidate pixels. Correspondingly, a similar method can be used to obtain the first color feature value for the calibration image, which can specifically include: a first color feature value for the red chromaticity component and a first color feature value for the blue chromaticity component.

[0147] In one possible implementation, the determination of the second color feature value based on each candidate pixel includes the following steps S221 to S223:

[0148] S221: Determine the brightness value of each candidate pixel, and sort the candidate pixels in descending order of brightness value to obtain the sorting result.

[0149] Understandably, in the YUV color space, the color information of a pixel is decomposed into a luminance component (Y) and a chrominance component (Cr and Cb). Therefore, the luminance value of each candidate pixel can be the luminance component value Y in the YUV color space. Furthermore, after obtaining the luminance values ​​of all candidate pixels, all candidate pixels are sorted in descending order of luminance value.

[0150] S222: Based on the sorting results, select the candidate pixels that are in the top preset percentage as each reference pixel.

[0151] The preset percentage can be pre-defined, for example, set to 10%. This allows the top 10% of candidate pixels to be selected as reference pixels based on the sorting results. Each reference pixel has a relatively high brightness value, meaning they are generally brighter, and the second color feature values ​​determined based on these reference pixels are more accurate.

[0152] S223: Determine the second color feature value based on each reference pixel.

[0153] In this example, when determining the second color feature value, the color channel values ​​of other pixels are not considered; only the reference pixels with higher brightness values ​​are considered.

[0154] Considering that noise in an image typically causes random fluctuations in pixel values, this effect is more pronounced in low-brightness areas due to lower signal strength and a lower signal-to-noise ratio. In contrast, high-brightness areas have higher signal strength and a higher signal-to-noise ratio, and are therefore less affected by noise. Therefore, the accuracy of the second color feature value determined based on reference pixels with higher brightness values ​​is higher. Furthermore, high-brightness areas exhibit better color consistency; color variations are typically smaller and more uniform under different background and lighting conditions, making the second color feature value determined based on reference pixels with higher brightness values ​​more reliable.

[0155] In one possible implementation, the second color feature value is a color feature value in the RGB color space. The determination of the second color feature value based on each reference pixel includes the following steps S41 to S43:

[0156] S41: Calculate the average value of the second red channel in the second color feature value by averaging the red channel values ​​of each reference pixel.

[0157] S42: Calculate the average of the green channel values ​​of each reference pixel to obtain the average value of the second green channel in the second color feature value.

[0158] S43: Calculate the average value of the second blue channel in the second color feature value by averaging the blue channel values ​​of each reference pixel.

[0159] Understandably, in the RGB color space, each reference pixel has a red channel value (R value), a green channel value (G value), and a blue channel value (B value). Based on this, the second red channel average value (R_ave_2) is obtained by averaging the R values ​​of all reference pixels, the second green channel average value (G_ave_2) is obtained by averaging the G values ​​of all reference pixels, and the second blue channel average value (B_ave_2) is obtained by averaging the B values ​​of all reference pixels.

[0160] In this implementation, the second color feature values ​​include: R_ave_2, G_ave_2, and B_ave_2. Similarly, for the calibration image, the first color feature value is the color feature value in the RGB color space. The first color feature value can be determined using a similar method as the second color feature value. This first color feature value includes: the average value of the first red channel (R_ave_1), the average value of the first green channel (G_ave_1), and the average value of the first blue channel (B_ave_1).

[0161] In this implementation, the first color feature value can specifically be: the average color value of the reference pixels in the optical-mechanical image area of ​​the calibration image in the RGB color space, including: the average value of the first red channel (i.e., the average value of the red channel of the reference pixels in the optical-mechanical image area of ​​the calibration image), the average value of the first green channel (i.e., the average value of the green channel of the reference pixels in the optical-mechanical image area of ​​the calibration image), and the average value of the first blue channel (i.e., the average value of the blue channel of the reference pixels in the optical-mechanical image area of ​​the calibration image). The second color feature value can specifically be: the average color value of the reference pixels in the optical-mechanical image area of ​​the target image, including: the average value of the second red channel (i.e., the average value of the red channel of the reference pixels in the optical-mechanical image area of ​​the target image), the average value of the second green channel (i.e., the average value of the green channel of the reference pixels in the optical-mechanical image area of ​​the target image), and the average value of the second blue channel (i.e., the average value of the blue channel of the reference pixels in the optical-mechanical image area of ​​the target image).

[0162] In one possible implementation, the second color feature value is a color feature value in the YUV color space. The determination of the second color feature value based on each reference pixel includes the following steps S51 to S52:

[0163] S51: Calculate the average value of the second red chromaticity component in the second color feature value by averaging the red chromaticity component values ​​of each reference pixel.

[0164] S52: Calculate the average value of the second blue chromaticity component in the second color feature value by averaging the blue chromaticity component values ​​of each reference pixel.

[0165] Understandably, in the YUV color space, each reference pixel has a red chromaticity component value (Cr value) and a blue chromaticity component value (Cb value). Based on this, the second average value of the red chromaticity component (Cr_ave_2) is obtained by averaging the Cr values ​​of all reference pixels, and the second average value of the blue chromaticity component (Cb_ave_2) is obtained by averaging the Cb values ​​of all reference pixels.

[0166] In this implementation, the second color feature values ​​include Cr_ave_2 and Cb_ave_2. Similarly, for the calibration image, the first color feature value is the color feature value in the YUV color space. The first color feature value can be determined in a similar way to the determination of the second color feature value. The first color feature value includes the average value of the first red chromaticity component (Cr_ave_1) and the average value of the first blue chromaticity component (Cb_ave_1).

[0167] In this implementation, the first color feature value can specifically be: the average color value of the reference pixels in the optical-mechanical image area of ​​the calibration image in the YUV color space, including: the average value of the first red chromaticity component (i.e., the average value of the red chromaticity component of the reference pixels in the optical-mechanical image area of ​​the calibration image) and the average value of the first blue chromaticity component (i.e., the average value of the blue chromaticity component of the reference pixels in the optical-mechanical image area of ​​the calibration image). The second color feature value can specifically be: the average color value of the reference pixels in the optical-mechanical image area of ​​the target image, including: the average value of the second red chromaticity component (i.e., the average value of the red chromaticity component of the reference pixels in the optical-mechanical image area of ​​the target image) and the average value of the second blue chromaticity component (i.e., the average value of the blue chromaticity component of the reference pixels in the optical-mechanical image area of ​​the target image).

[0168] It should be noted that the determination method of the second color feature value has been explained in detail above. In the specific implementation, the determination method of the first color feature value is basically the same as that of the second color feature value. The difference is that the second color feature value is calculated based on the optical-mechanical screen area in the target image, while the first color feature value is calculated based on the optical-mechanical screen area in the calibration image. To avoid repetition, the specific determination method of the first color feature value will not be repeated here. Please refer to the specific determination method of the second color feature value mentioned above.

[0169] In step 103, the ratio obtained based on the first color feature value and the second color feature value is acquired.

[0170] In one possible implementation, both the first color feature value and the second color feature value are color feature values ​​in the RGB color space. The first color feature value includes: the average value of the first red channel (R_ave_1), the average value of the first green channel (G_ave_1), and the average value of the first blue channel (B_ave_1). The second color feature value includes: the average value of the second red channel (R_ave_2), the average value of the second green channel (G_ave_2), and the average value of the second blue channel (B_ave_2). In this case, step 103 is implemented as follows:

[0171] Get the first ratio between R_ave_1 and R_ave_2 (R_ave_1 / R_ave_2);

[0172] Obtain the second ratio (G_ave_1 / G_ave_2) between G_ave_1 and G_ave_2;

[0173] Obtain the third ratio (B_ave_1 / B_ave_2) between B_ave_1 and B_ave_2.

[0174] In other words, in this implementation, the ratios obtained based on the first color feature value and the second color feature value include: R_ave_1 / R_ave_2, G_ave_1 / G_ave_2, and B_ave_1 / B_ave_2.

[0175] In another possible implementation, both the first and second color feature values ​​are color feature values ​​in the YUV color space. The first color feature value includes: the average value of the first red chromaticity component (Cr_ave_1) and the average value of the first blue chromaticity component (Cb_ave_1). The second color feature value includes: the average value of the second red chromaticity component (Cr_ave_2) and the average value of the second blue chromaticity component (Cb_ave_2). In this case, step 103 is implemented as follows:

[0176] Obtain the fourth ratio (Cr_ave_1 / Cr_ave_2) between Cr_ave_1 and Cr_ave_2;

[0177] Obtain the fifth ratio (Cb_ave_1 / Cb_ave_2) between Cb_ave_1 and Cb_ave_2.

[0178] In other words, in this implementation, the ratios obtained based on the first color feature value and the second color feature value include: Cr_ave_1 / Cr_ave_2 and Cb_ave_1 / Cb_ave_2.

[0179] In step 104, the target color gain of the projection device in the usage scenario is determined based on the aforementioned ratio and luminance loss. The luminance loss is determined either based on the ratio or based on the projection display brightness of the projection device. The luminance loss characterizes the reduction in projection display brightness that would result from correcting the projection device based on the ratio. Alternatively, the luminance loss characterizes the impact of correcting the projection device based on the ratio on the projection display brightness. The projection display brightness is the brightness of the image displayed on the second projection background when any image to be projected is projected by the projection device. This image to be projected can be the aforementioned preset solid color image or other images; this embodiment does not specifically limit the specific type of image.

[0180] Color gain is a software parameter of a projection device. In the usage scenarios of a projection device, by adjusting the color gain of the projection device, the projected image can present different color effects when any image is projected onto a second projection background.

[0181] Using the aforementioned target ratio as the target color gain for the projection device in the usage scenario can be understood as follows: The target ratio is input into the projection device so that it uses this ratio as the target color gain for the usage scenario. This allows the projection device to adjust its original color gain to the target color gain, thus completing the adaptive color adjustment for the usage scenario. Both the original color gain and the target color gain refer to the color gain of the projection device. The difference lies in the following: the original color gain refers to the color gain already configured on the projection device before performing adaptive color adjustment for the current usage scenario. The target color gain refers to the target ratio, which can be understood as the updated color gain of the projection device after performing adaptive color adjustment for the current usage scenario. In this embodiment, the color gain is used to change the hue of the image colors.

[0182] In this embodiment, adjusting the original color gain to the target color gain is a software-level adjustment. Changing the color gain of the projection device at the software level adjusts the color ratio parameters of the image projected onto the usage scene. This software-level color gain adjustment differs from hardware-level color adjustment achieved by adjusting the current coefficient of the projection lamp. This embodiment does not require adjusting the voltage or current of the projection optical engine at the hardware level to achieve color adjustment.

[0183] In one possible implementation, after obtaining the ratio based on the first color feature value and the second color feature value, the method further includes: determining whether there is a brightness loss between the projected display brightness obtained after correction based on the ratio and the projected display brightness before correction. Correspondingly, the above-mentioned determination of the target color gain of the projector in the usage scenario based on the ratio and brightness loss includes: if there is a brightness loss, performing brightness compensation based on the ratio to obtain the target ratio, and using the target ratio as the target color gain of the projector in the usage scenario;

[0184] If there is no brightness loss, then the ratio is taken as the target color gain of the projection device in the usage scenario.

[0185] In this implementation, the brightness loss is determined based on the projected display brightness. The projected display brightness is the brightness of the image displayed on the second projection background when any image to be projected is projected onto the projection device.

[0186] The pre-correction projection display brightness can be understood as follows: a projection device configured with original color gain (color gain without ratio correction) projects an image onto a second projection background, and the brightness of the projected image is captured by the camera built into the projection device. For example, when the image to be projected is the aforementioned preset solid color image, the pre-correction projection display brightness can be the brightness of the target image.

[0187] The projection display brightness obtained after ratio correction can be understood as follows: the projection device, which uses the ratio as the target color gain to update the original color gain, projects an image to be projected onto a second projection background, and uses the built-in camera of the projection device to capture the brightness of the projected image.

[0188] In the above-mentioned method for determining brightness loss, the image corresponding to the projection display brightness before correction is the same as the image corresponding to the projection display brightness after ratio correction.

[0189] The following is a further explanation of how the projection display brightness is determined after the above ratio correction:

[0190] For example, the second color feature value can be corrected based on the ratio and the second color feature value to obtain a corrected third color feature value. Then, the brightness corresponding to the third color feature value is calculated, and this brightness is used as the projection display brightness obtained after correction based on the ratio. For ease of understanding, a specific example is provided below:

[0191] For example, the second color feature value includes the average values ​​of the second red channel (R_ave_2), the second green channel (G_ave_2), and the second blue channel (B_ave_2) mentioned above, and the ratio includes obtaining the first ratio, the second ratio, and the third ratio mentioned above. In this case, the third color feature value includes: the average value of the third red channel obtained by multiplying (R_ave_2) by the first ratio (R_ave_3), the average value of the third green channel obtained by multiplying (G_ave_2) by the second ratio (G_ave_3), and the average value of the third blue channel obtained by multiplying (B_ave_2) by the third ratio (B_ave_3). It can be understood that since there is a conversion relationship between the three color channel values ​​in the RGB color space and the brightness, the brightness corresponding to the third color feature value can be calculated based on the third color feature value (R_ave_3, G_ave_3, B_ave_3) and the above conversion relationship.

[0192] For example, this ratio can also be input into the projection device as the test color gain of the projection device. Then, under the action of this test color gain, a preset pure color image is projected again onto the second projection background through the projection device, and a corrected image is captured by a camera. The brightness of this corrected image is used as the projection display brightness obtained after the projection device is corrected based on the above ratio. Next, it can be determined whether there is a brightness difference between the target image and the corrected image. For example, it can be determined whether the brightness of the corrected image is reduced compared to the target image. If there is a brightness reduction, it means that there is a brightness loss, that is, the test color gain cannot be used as the target color gain suitable for the usage scenario. If there is no brightness reduction, it means that there is no brightness loss, that is, the test color gain can be used as the target color gain suitable for the usage scenario.

[0193] If the projected display brightness after ratio correction is significantly lower than the original brightness, it indicates that the correction process may have introduced unnecessary brightness loss, requiring brightness compensation. Brightness compensation helps ensure that the image maintains good visual quality after color correction, preventing the reduced brightness from negatively impacting the user's viewing experience. By considering both color correction and brightness compensation simultaneously, it's possible to maintain color accuracy while ensuring the overall image brightness remains as close as possible to its original level. This avoids sacrificing image brightness for color accuracy, achieving an optimal balance between color and brightness for a more realistic and natural visual experience.

[0194] In this embodiment of the application, the projection display brightness obtained after the above ratio correction reflects the display brightness of the image projected onto the second projection background by the projection device after the ratio is used as the target color gain to correct the projection device. Therefore, whether there is a brightness loss between the projection display brightness obtained after correction and the projection display brightness before correction is helpful to accurately determine whether brightness compensation is needed in the current usage scenario.

[0195] If there is a loss of brightness, then brightness compensation is required. If there is no loss of brightness, then brightness compensation is not required.

[0196] When brightness compensation is not required, it is explained that if the ratio is directly used as the target color gain, the image adjusted by this target color gain will not suffer from brightness loss. Therefore, the ratio can be directly used as the target color gain. However, when brightness compensation is required, it is explained that if the ratio is directly used as the target color gain, the image adjusted by this target color gain may suffer from brightness loss. Therefore, the ratio is not directly used as the target color gain. Instead, brightness compensation is performed based on the ratio to obtain the target ratio, and this target ratio is used as the target color gain. This helps to reduce or avoid potential brightness loss in the image adjusted by this target color gain.

[0197] In one possible implementation, the aforementioned ratios include: a first ratio (R_ave_1 / R_ave_2), a second ratio (G_ave_1 / G_ave_2), and a third ratio (B_ave_1 / B_ave_2) calculated in the RGB color space. In this case, after obtaining the ratios based on the first and second color feature values, the method further includes: if the first, second, and third ratios are all greater than or equal to 1, determining that there is no luminance loss; if the first, second, or third ratio is less than 1, determining that there is luminance loss. Correspondingly, determining the target color gain of the projection device in the usage scenario based on the ratios and luminance loss includes: if luminance loss is determined to exist, performing luminance compensation based on the ratios to obtain a target ratio, and using the target ratio as the target color gain of the projection device in the usage scenario; if no luminance loss is determined to exist, using the ratio as the target color gain of the projection device in the usage scenario.

[0198] In this implementation, the brightness loss is determined based on ratios. It's understandable that when the target color gain of a certain color channel is less than 1, the overall brightness of the projected image will decrease, meaning the projection display brightness of the projector will also decrease. Therefore, if the first, second, or third ratio is less than 1, it means that using these ratios as the target color gains for the three color channels will result in a decrease in the projection display brightness, thus confirming the existence of brightness loss. To avoid the dimming of the projected display and its impact on user experience, brightness compensation is necessary when brightness loss exists. The brightness compensation method is as follows: perform brightness compensation based on ratios to obtain the target ratio, and use this target ratio as the target color gain for the projector in the usage scenario.

[0199] If the first, second, and third ratios are all greater than or equal to 1, it means that using these three ratios as the target color gain for the three color channels will not cause the overall brightness of the projected image to darken, thus confirming that there is no brightness loss. Since there is no brightness loss, the user experience will not be affected, and therefore brightness compensation is unnecessary. When brightness compensation is not required, the ratios can be directly used as the target color gain for the projection device in the usage scenario.

[0200] In one possible implementation, the aforementioned ratio is obtained based on the first and second color feature values ​​in the RGB color space, and this ratio includes the first, second, and third ratios mentioned above. Correspondingly, using the ratios as the target color gain of the projection device in the usage scenario includes: using the first ratio as the target color gain of the red channel of the projection device in the usage scenario; using the second ratio as the target color gain of the green channel of the projection device in the usage scenario; and using the third ratio as the target color gain of the blue channel of the projection device in the usage scenario.

[0201] The projection device achieves adaptive color adjustment for different usage scenarios by adjusting the original color gain of each color channel to the corresponding target color gain. For example, suppose the original color gains of the three color channels of the projection device are 1, 1, and 1, and the RGB values ​​of the three color channels are (255, 255, 255). If the target color gains of the three color channels obtained through the embodiments of this application are 1, 1.2, and 1.3, then the RGB values ​​of the three color channels (255, 255, 255) become (255*1, 255*1.2, 255*1.3) after adjustment by the target color gain.

[0202] In another possible implementation, the aforementioned ratios are obtained based on the first and second color feature values ​​in the YUV color space. These ratios include a fourth ratio between the average value of the first red chromaticity component and the average value of the second red chromaticity component, and a fifth ratio between the average value of the first blue chromaticity component and the average value of the second blue chromaticity component. Correspondingly, determining the target color gain of the projection device in the usage scenario based on the aforementioned ratios and luminance loss includes: if there is no luminance loss, then using the fourth ratio as the target color gain of the red chromaticity component of the projection device in the usage scenario, and using the fifth ratio as the target color gain of the blue chromaticity component of the projection device in the usage scenario.

[0203] The projection device achieves adaptive color adjustment for the application scenario by adjusting the original color gain of the blue chromaticity component to the target color gain of the blue chromaticity component, and adjusting the original color gain of the red chromaticity component to the target color gain of the red chromaticity component, while maintaining the original gain of the luminance component unchanged. Maintaining the original gain of the luminance component unchanged avoids luminance loss after adaptive color adjustment. In other words, if the original gain of the luminance component remains unchanged, it can be determined that there is no luminance loss.

[0204] In this embodiment, when brightness compensation is required, it is explained that if the ratio is directly used as the target color gain, the image adjusted by the target color gain will suffer from brightness loss. Therefore, brightness compensation is necessary to reduce or avoid this loss. The brightness compensation method is as follows: brightness compensation is performed based on the aforementioned ratio to obtain a target ratio, and this target ratio is used as the target color gain for the projection device in the usage scenario. Specifically, the aforementioned target ratio is input into the projection device so that the projection device uses this target ratio as the target color gain for the usage scenario. This allows the projection device to adjust the original color gain to the target color gain, completing the adaptive color adjustment for the usage scenario.

[0205] In one possible implementation, the target ratio obtained through brightness compensation includes a first target ratio, a second target ratio, and a third target ratio. Brightness compensation is performed based on these ratios to obtain the target ratio, and this target ratio is used as the target color gain of the projection device in the stated usage scenario, including the following steps S61 to S66:

[0206] S61: Multiply the first ratio by the target coefficient to obtain the first target ratio.

[0207] S62: Multiply the second ratio by the target coefficient to obtain the second target ratio.

[0208] S63: Multiply the third ratio by the target coefficient to obtain the third target ratio.

[0209] S64: Use the first target ratio as the target color gain of the red channel in the usage scenario of the projection device.

[0210] S65: Use the second target ratio as the target color gain of the green channel in the usage scenario of the projection device.

[0211] S66: Use the third target ratio as the target color gain of the blue channel in the usage scenario of the projection device.

[0212] Among them, the first target ratio, the second target ratio, and the third target ratio are all greater than or equal to 1. The above target coefficients are any values ​​that make the first target ratio, the second target ratio, and the third target ratio all greater than or equal to 1.

[0213] In this embodiment, since the first target ratio, the second target ratio, and the third target ratio are all greater than or equal to 1, the final determined target color gain for each color channel is greater than or equal to 1. This ensures that the image brightness after target color gain correction has minimal brightness loss compared to the image brightness before correction, thus improving the user's visual experience. The image brightness before and after target color gain correction can be understood as the projection display brightness obtained by the projection device based on the target color gain correction.

[0214] In one possible implementation, the target coefficient is determined as follows: the minimum ratio is determined among the first ratio, the second ratio, and the third ratio; the quotient obtained by dividing 1 by the minimum ratio is used as the target coefficient.

[0215] For example, if the first, second, and third ratios calculated so far are 0.8, 1.1, and 1.2 respectively, then the minimum ratio is 0.8, and the target coefficient can be 1 / 0.8. Based on this, the first, second, and third target ratios calculated are 1, 1.1 / 0.8, and 1.2 / 0.8 respectively. If the RGB values ​​before color correction are (255, 255, 25), then the RGB values ​​after color correction using the target color gain of each color channel are (255*1, 255*1.1 / 0.8, 255*1.2 / 0.8).

[0216] In this embodiment, the quotient obtained by dividing 1 by the minimum ratio is used as the target coefficient, which is equivalent to normalization using the minimum ratio. This can maintain the relative gain ratio between each color channel, thus ensuring that the overall color balance is not destroyed, making the corrected color look more natural, avoiding color distortion caused by excessive color gain of a single color channel, and improving the accuracy of color correction.

[0217] Figure 6 is a schematic flowchart of another projection control method provided in an embodiment of this application.

[0218] For example, as shown in Figure 6, this projection control method mainly includes three components: the first part is the factory-stored calibration data; the second part is the calculation of the optical-mechanical image area in the camera image; and the third part is the calculation of the target color gain. These three parts are explained below:

[0219] Part 1: Factory maintains calibration data.

[0220] In the calibration scenario, the preset solid color image is a pure white image, and the first projection background is a white wall or a white screen. The pure white image is projected onto the white wall (or white screen) using a projection device, and then a picture is taken using the built-in camera of the projection device to obtain the calibration image (denoted as camera image 1). The calibration data is saved in two forms: the first is to save the calibration image to the memory of the projection device, and the second is to save the first color feature values ​​(such as R_ave_1, G_ave_1, and B_ave_1 mentioned above) calculated based on the calibration image to the memory of the projection device.

[0221] Part Two: Calculate the optical-mechanical field of view in the camera image.

[0222] The camera image refers to the image captured using the camera built into the projector. The purpose of this step is to determine the optical-mechanical field of view of the image captured by the projector's built-in camera, thereby ignoring non-optical-mechanical areas in the camera image to improve the accuracy of finding reference pixels.

[0223] In the calibration scenario, the preset feature image is a checkerboard image. The checkerboard image is projected onto the third projection background through a projection device, and then a photo is taken using the built-in camera of the projection device to obtain a reference image (denoted as camera image 2).

[0224] Extract the corner points of the original checkerboard image, denoted as corner point 1. Extract the corner points of camera image 2, denoted as corner point 2. Based on the one-to-one correspondence between corner point 1 and corner point 2, the H matrix can be calculated. The H matrix can be used to transform the pixels on the optical-mechanical image onto the camera image.

[0225] The relationship between the optical-mechanical image (illustratively shown as a checkerboard pattern in Figure 5), the optical-mechanical screen area, and camera image 2 (illustratively shown as a reference image in Figure 5) can be seen in Figure 5. Assuming the projection device has a resolution of 1080P, the coordinates of the four corners of the optical-mechanical image are: x1(0,0), x2(1920,0), x3(1920,1080), x4(0,1080). The coordinates x1', x2', x3', and x4' of the four corners of the optical-mechanical image in camera image 2 can be obtained using the H matrix. These coordinates x1', x2', x3', and x4' can be used as the position coordinates of the optical-mechanical screen area in each image captured by the camera built into the projection device.

[0226] Part Three: Calculating the Target Color Gain. This part calculates the target color gain using a dynamic thresholding method, with the following steps:

[0227] S71: In the user's usage scenario, the projection device projects a pure white image onto the projection background in the usage scenario, and then takes a picture using the built-in camera of the projection device to obtain the target image (denoted as camera image 3).

[0228] S72: Use dynamic thresholding to find the reference white point for camera image 1 and camera image 3 respectively.

[0229] The reference white points obtained by using the dynamic thresholding method on camera image 3 can be the reference pixels selected from the target image as described above. Similarly, the reference white points obtained by using the dynamic thresholding method on camera image 1 can be the reference pixels selected from the calibration image.

[0230] For example, the process of determining the reference white point using a dynamic thresholding method on camera image 3 may include the following steps S721 to S727:

[0231] S721: Converts camera image 3 into a YUV (also known as YCrCb) image, and divides the optical and mechanical image area of ​​camera image 3 into 12 sub-regions (the optical and mechanical image area is the area within four points: x1', x2', x3', and x4').

[0232] S722: For each sub-region obtained by S721, calculate the mean value M1 of Cr and the mean value M2 of Cb for that sub-region.

[0233] S723: For each sub-region obtained by S721, calculate the standard deviation D1 of Cr and the standard deviation D2 of Cb in that sub-region.

[0234] S724: Select the target sub-regions from the 12 sub-regions obtained in S721 that meet the preset filtering conditions. The D1 of the target sub-region is greater than or equal to the first preset threshold, and the D2 of the target sub-region is greater than or equal to the second preset threshold.

[0235] S725: Calculate the average of M1 across all target sub-regions to obtain the first mean Mr, and calculate the average of M2 across all target sub-regions to obtain the second mean Mb.

[0236] S726: Based on formulas 3 and 4 above, select the pixels that meet the conditions as candidate white points in the optical and mechanical image area of ​​camera image 3.

[0237] S727: Sort the brightness values ​​Y of the candidate white points selected above from high to low, and select the top 10% of the points as reference white points.

[0238] The process of obtaining the reference white point from camera image 1 using the dynamic thresholding method is similar to S721 to S727 above. Simply replace camera image 3 involved in S721 to S727 with camera image 1 to obtain the reference white point in camera image 1. To avoid repetition, it will not be described in detail here.

[0239] S73: Calculate the first color feature value (R_ave_1, G_ave_1, B_ave_1) based on the RGB values ​​of the reference white point selected from camera image 1, and calculate the second color feature value (R_ave_2, G_ave_2, B_ave_2) based on the RGB values ​​of the reference white point selected from camera image 3.

[0240] S74: Obtain the ratio based on the first color feature value and the second color feature value. This ratio includes: R_ave_1 / R_ave_2, G_ave_1 / G_ave_2, and B_ave_1 / B_ave_2.

[0241] S75: When R_ave_1 / R_ave_2, G_ave_1 / G_ave_2, and B_ave_1 / B_ave_2 are all greater than or equal to 1, R_ave_1 / R_ave_2 is used as the target color gain R_gain for the red channel, G_ave_1 / G_ave_2 is used as the target color gain G_gain for the green channel, and B_ave_1 / B_ave_2 is used as the target color gain B_gain for the blue channel.

[0242] S76: When any of R_ave_1 / R_ave_2, G_ave_1 / G_ave_2, or B_ave_1 / B_ave_2 is less than 1, multiply these three ratios by the target coefficient m to obtain the target color gain for each color channel, including: R_gain = m * R_ave_1 / R_ave_2, G_gain = m * G_ave_1 / G_ave_2, B_gain = m * B_ave_1 / B_ave_2. R_gain, G_gain, and B_gain are all greater than or equal to 1.

[0243] This application proposes a method for determining a reference white point based on a dynamic threshold. This method can accurately locate the reference white point against complex backgrounds, thereby ensuring optimal color adaptation and offering greater flexibility and accuracy. Furthermore, by extracting the optical-mechanical image area from the camera image, non-optical-mechanical image areas can be accurately filtered out, thus improving the accuracy and efficiency of color adaptation.

[0244] Figure 7 is a schematic diagram of the structure of a projection control device provided in an embodiment of this application.

[0245] For example, as shown in FIG7, the projection control device 700 includes:

[0246] The first acquisition module 701 is used to acquire a first color feature value; wherein the first color feature value is obtained by projecting a preset solid color image onto a first projection background through a projection device; the first projection background is located in the calibration scene of the projection device.

[0247] The determining module 702 is used to determine the second color feature value of the optical-mechanical screen area in the target image; wherein the target image is obtained by the projection device projecting the preset pure color image onto the second projection background and then taking a picture using the camera built into the projection device; the second projection background is located in the usage scenario of the projection device.

[0248] The second acquisition module 703 is used to acquire the ratio obtained based on the first color feature value and the second color feature value.

[0249] The color gain determination module 704 is used to determine the target color gain of the projection device in the above-mentioned usage scenario based on the above-mentioned ratio and brightness loss; wherein the above-mentioned brightness loss is determined based on the above-mentioned ratio or based on the projection display brightness of the above-mentioned projection device, and the above-mentioned projection display brightness is the display brightness of the screen on the second projection background where the projection device projects any image to be projected.

[0250] In one possible implementation, the projection control device 700 further includes: a judgment module, configured to, after obtaining the ratio based on the first color feature value and the second color feature value, determine whether there is a brightness loss between the projection display brightness obtained by the projection device after correction based on the ratio and the projection display brightness before correction; and a color gain determination module 704, specifically configured to: if there is a brightness loss, perform brightness compensation based on the ratio to obtain a target ratio, and use the target ratio as the target color gain of the projection device in the usage scenario; if there is no brightness loss, use the ratio as the target color gain of the projection device in the usage scenario.

[0251] In one possible implementation, the first color feature value includes: the average value of the first red channel, the average value of the first green channel, and the average value of the first blue channel; the second color feature value includes: the average value of the second red channel, the average value of the second green channel, and the average value of the second blue channel; the ratio includes: a first ratio between the average value of the first red channel and the average value of the second red channel, a second ratio between the average value of the first green channel and the average value of the second green channel, and a third ratio between the average value of the first blue channel and the average value of the second blue channel; the projection control device 700 further includes: a brightness loss determination module, used to determine that there is no brightness loss when the first ratio, the second ratio, and the third ratio are all greater than or equal to 1; and to determine that there is brightness loss when the first ratio, the second ratio, or the third ratio is less than 1; a color gain determination module 704, specifically used to perform brightness compensation based on the ratio when brightness loss is determined to exist, obtain a target ratio, and use the target ratio as the target color gain of the projection device in the usage scenario; and to use the ratio as the target color gain of the projection device in the usage scenario when there is no brightness loss.

[0252] In one possible implementation, the color gain determination module 704 is specifically used to take the first ratio of the above ratios as the target color gain of the red channel of the projection device in the above usage scenario; take the second ratio of the above ratios as the target color gain of the green channel of the projection device in the above usage scenario; and take the third ratio of the above ratios as the target color gain of the blue channel of the projection device in the above usage scenario.

[0253] In one possible implementation, the target ratio includes a first target ratio, a second target ratio, and a third target ratio; the color gain determination module 704 is specifically used to: multiply the first ratio by a target coefficient to obtain the first target ratio; multiply the second ratio by the target coefficient to obtain the second target ratio; multiply the third ratio by the target coefficient to obtain the third target ratio; wherein the first target ratio, the second target ratio, and the third target ratio are all greater than or equal to 1; the first target ratio is used as the target color gain of the red channel of the projection device in the above usage scenario; the second target ratio is used as the target color gain of the green channel of the projection device in the above usage scenario; and the third target ratio is used as the target color gain of the blue channel of the projection device in the above usage scenario.

[0254] In one possible implementation, the projection control device 700 further includes: a target coefficient determination module, used to determine the minimum ratio among the first ratio, the second ratio, and the third ratio; and to use the quotient obtained by dividing 1 by the minimum ratio as the target coefficient.

[0255] In one possible implementation, the first color feature value includes: the average value of the first red chromaticity component and the average value of the first blue chromaticity component; the second color feature value includes: the average value of the second red chromaticity component and the average value of the second blue chromaticity component; the ratio includes: a fourth ratio between the average value of the first red chromaticity component and the average value of the second red chromaticity component, and a fifth ratio between the average value of the first blue chromaticity component and the average value of the second blue chromaticity component; the color gain determination module 704 is specifically used to: if there is no brightness loss, take the fourth ratio as the target color gain of the red chromaticity component of the projection device in the above usage scenario, and take the fifth ratio as the target color gain of the blue chromaticity component of the projection device in the above usage scenario.

[0256] In one possible implementation, the projection control device 700 further includes: a position coordinate determination module, used to determine the position coordinates of the optical-mechanical screen area in the reference image; wherein the reference image is obtained by the camera after the projection device projects a preset feature image onto the third projection background; and the optical-mechanical screen area determination module is used to determine the optical-mechanical screen area in the target image based on the position coordinates.

[0257] In one possible implementation, the position coordinate determination module is specifically used to extract a first feature point from the preset feature image; extract a second feature point in the reference image corresponding to the first feature point; determine a projection transformation matrix based on the first and second feature points; determine the coordinates of the boundary points of the preset feature image based on the resolution of the projection device; and perform a projection transformation on the coordinates of the boundary points of the preset feature image based on the projection transformation matrix to obtain the position coordinates of the optical-mechanical screen area in the reference image.

[0258] In one possible implementation, the memory of the projection device stores a calibration image, which is obtained by the projection device projecting a preset solid color image onto the first projection background and then capturing it with the camera; the first acquisition module 701 is specifically used to acquire the calibration image from the memory and determine a first color feature value of the optical-mechanical screen area in the calibration image.

[0259] In one possible implementation, the first color feature value is stored in the memory of the projection device; the first acquisition module 701 is specifically used to acquire the first color feature value from the memory.

[0260] In one possible implementation, the determining module 702 is specifically used to: filter out each candidate pixel in the optical-mechanical image region of the target image based on a dynamic threshold; wherein the dynamic threshold is determined based on the chromaticity components of each pixel in the optical-mechanical image region; the closeness between the color of each candidate pixel and the color of the preset pure color image is greater than a preset degree threshold; and determine the second color feature value based on each candidate pixel.

[0261] In one possible implementation, the determining module 702 is specifically used to: determine the brightness value of each candidate pixel, and sort the candidate pixels in descending order of brightness value to obtain a sorting result; select the candidate pixels in the top preset percentage as reference pixels based on the sorting result; and determine the second color feature value based on the reference pixels.

[0262] In one possible implementation, determining the second color feature value based on each of the reference pixels includes: averaging the red channel values ​​of each of the reference pixels to obtain a second red channel average value in the second color feature value; averaging the green channel values ​​of each of the reference pixels to obtain a second green channel average value in the second color feature value; averaging the blue channel values ​​of each of the reference pixels to obtain a second blue channel average value in the second color feature value; or averaging the red chromaticity component values ​​of each of the reference pixels to obtain a second red chromaticity component average value in the second color feature value; averaging the blue chromaticity component values ​​of each of the reference pixels to obtain a second blue chromaticity component average value in the second color feature value.

[0263] In one possible implementation, the dynamic threshold includes: a dynamic threshold corresponding to the red chromaticity component in the target image and a dynamic threshold corresponding to the blue chromaticity component in the target image; the dynamic threshold corresponding to the red chromaticity component in the target image is determined based on the red chromaticity component of each pixel in the optical-mechanical image area of ​​the target image; the dynamic threshold corresponding to the blue chromaticity component in the target image is determined based on the blue chromaticity component of each pixel in the optical-mechanical image area of ​​the target image.

[0264] In one possible implementation, the projection control device 700 further includes a dynamic threshold determination module, configured to: divide the optical-mechanical screen area of ​​the target image into multiple sub-regions; calculate the mean value of the red chromaticity component and the mean value of the blue chromaticity component of each sub-region; calculate the standard deviation of the red chromaticity component and the standard deviation of the blue chromaticity component of each sub-region; select sub-regions that meet preset screening conditions from the multiple sub-regions as target sub-regions; wherein the standard deviation of the red chromaticity component of the target sub-region is greater than or equal to a first preset threshold, and the standard deviation of the blue chromaticity component of the target sub-region is greater than or equal to a second preset threshold; average the mean values ​​of the red chromaticity components of all target sub-regions to obtain a first mean value, and average the mean values ​​of the blue chromaticity components of all target sub-regions to obtain a second mean value; The standard deviations of the red chromaticity components of all target sub-regions are averaged to obtain a third mean, and the standard deviations of the blue chromaticity components of all target sub-regions are averaged to obtain a fourth mean. Based on the first and third means, the dynamic threshold corresponding to the red chromaticity components in the target image is determined. Based on the second and fourth means, the dynamic threshold corresponding to the blue chromaticity components in the target image is determined.

[0265] In one possible implementation, the preset solid color image is a pure white image, and the first projection background is a pure white projection background.

[0266] Figure 8 is a schematic diagram of the structure of a projection device provided in an embodiment of this application.

[0267] As exemplarily shown in FIG8, the projection device 800 includes a memory 801 and a processor 802, wherein the memory 801 stores executable program code 8011, and the processor 802 is used to call and execute the executable program code 8011 to perform a projection control method.

[0268] Furthermore, embodiments of this application also protect an apparatus that may include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to perform a projection control method provided in embodiments of this application.

[0269] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0270] When each functional module is divided according to its corresponding function, the device may further include: a first acquisition module, a determination module, a second acquisition module, a color gain determination module, etc. It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0271] It should be understood that the device provided in this embodiment is used to execute the above-described projection control method, and therefore can achieve the same effect as the above-described implementation method.

[0272] When using integrated units, the device may include a processing module and a storage module. When applied to a projection device, the processing module can be used to control and manage the operation of the projection device. The storage module can be used to support the execution of relevant program code by the projection device.

[0273] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits shown in conjunction with the disclosure of this application. The processor may also be a combination of functions that implement computing capabilities, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc., and the storage module may be a memory.

[0274] In addition, the device provided in the embodiments of this application may specifically be a chip, component or module. The chip may include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute a projection control method provided in the above embodiments.

[0275] This embodiment also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer, the computer executes the above-described related method steps to implement a projection control method provided in the above embodiment.

[0276] This embodiment also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned related steps to implement a projection control method provided in the above embodiment.

[0277] In this embodiment, the device, computer-readable storage medium, computer program product, or chip are all used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0278] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0279] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0280] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

A projection control method is applied to a projection device, the projection device having a built-in camera, the method comprising: A first color feature value is obtained; wherein the first color feature value is obtained by projecting a preset solid color image onto a first projection background using the projection device; the first projection background is located in the calibration scene of the projection device. Determine a second color feature value for the optical-mechanical image region in the target image; wherein, the target image is obtained by the camera after the preset solid color image is projected onto a second projection background by the projection device; the second projection background is located in the usage scenario of the projection device; Obtain the ratio based on the first color feature value and the second color feature value; Based on the ratio and luminance loss, the target color gain of the projection device in the usage scenario is determined; wherein, the luminance loss is determined based on the ratio or based on the projection display luminance of the projection device, and the projection display luminance is the display luminance of the image projected by the projection device onto the second projection background. According to the method of claim 1, wherein, After obtaining the ratio based on the first color feature value and the second color feature value, the method further includes: Determine whether there is a brightness loss between the projected display brightness obtained by the projection device after correction based on the ratio and the projected display brightness before correction; Determining the target color gain of the projection device in the usage scenario based on the ratio and luminance loss includes: If the brightness loss exists, brightness compensation is performed based on the ratio to obtain a target ratio, and the target ratio is used as the target color gain of the projection device in the usage scenario. The method according to claim 2, wherein, The step of determining the target color gain of the projection device in the usage scenario based on the ratio and luminance loss further includes: If there is no brightness loss, then the ratio is taken as the target color gain of the projection device in the usage scenario. According to the method of claim 1, wherein, The first color feature value includes: the average value of the first red channel, the average value of the first green channel, and the average value of the first blue channel; the second color feature value includes: the average value of the second red channel, the average value of the second green channel, and the average value of the second blue channel; the ratio includes: a first ratio between the average value of the first red channel and the average value of the second red channel, a second ratio between the average value of the first green channel and the average value of the second green channel, and a third ratio between the average value of the first blue channel and the average value of the second blue channel; After obtaining the ratio based on the first color feature value and the second color feature value, the method further includes: If the first ratio, the second ratio, and the third ratio are all greater than or equal to 1, it is determined that there is no brightness loss. Determining the target color gain of the projection device in the usage scenario based on the ratio and luminance loss includes: If it is determined that there is no brightness loss, the ratio is taken as the target color gain of the projection device in the usage scenario. According to the method of claim 1, wherein, The first color feature value includes: the average value of the first red channel, the average value of the first green channel, and the average value of the first blue channel; the second color feature value includes: the average value of the second red channel, the average value of the second green channel, and the average value of the second blue channel; the ratio includes: a first ratio between the average value of the first red channel and the average value of the second red channel, a second ratio between the average value of the first green channel and the average value of the second green channel, and a third ratio between the average value of the first blue channel and the average value of the second blue channel; After obtaining the ratio based on the first color feature value and the second color feature value, the method further includes: If the first ratio, the second ratio, or the third ratio is less than 1, it is determined that there is a loss of brightness; Determining the target color gain of the projection device in the usage scenario based on the ratio and luminance loss includes: If the brightness loss is determined to exist, brightness compensation is performed based on the ratio to obtain a target ratio, and the target ratio is used as the target color gain of the projection device in the usage scenario. The method according to claim 4, wherein, The step of using the ratio as the target color gain of the projection device in the usage scenario includes: The first ratio in the ratio is taken as the target color gain of the red channel of the projection device in the usage scenario; The second ratio in the ratio is taken as the target color gain of the green channel of the projection device in the usage scenario; The third ratio in the ratio is taken as the target color gain of the blue channel of the projection device in the usage scenario. The method according to claim 5, wherein, The target ratio includes a first target ratio, a second target ratio, and a third target ratio; The step of performing brightness compensation based on the ratio to obtain a target ratio, and using the target ratio as the target color gain of the projection device in the usage scenario, includes: The first target ratio is obtained by multiplying the first ratio by the target coefficient; The second target ratio is obtained by multiplying the second ratio by the target coefficient; The third target ratio is obtained by multiplying the third ratio by the target coefficient; wherein the first target ratio, the second target ratio, and the third target ratio are all greater than or equal to 1; The first target ratio is used as the target color gain of the red channel of the projection device in the usage scenario. The second target ratio is used as the target color gain of the green channel of the projection device in the usage scenario; The third target ratio is used as the target color gain of the blue channel of the projection device in the usage scenario. The method according to claim 7, wherein, The target coefficient is determined based on the following method: Determine the minimum ratio among the first ratio, the second ratio, and the third ratio; The quotient obtained by dividing 1 by the minimum ratio is taken as the target coefficient. According to the method of claim 1, wherein, The first color feature value includes: the average value of the first red chromaticity component and the average value of the first blue chromaticity component; the second color feature value includes: the average value of the second red chromaticity component and the average value of the second blue chromaticity component; the ratio includes: a fourth ratio between the average value of the first red chromaticity component and the average value of the second red chromaticity component, and a fifth ratio between the average value of the first blue chromaticity component and the average value of the second blue chromaticity component; Determining the target color gain of the projection device in the usage scenario based on the ratio and luminance loss includes: If there is no brightness loss, then the fourth ratio in the ratio is taken as the target color gain of the red chromaticity component of the projection device in the usage scenario, and the fifth ratio in the ratio is taken as the target color gain of the blue chromaticity component of the projection device in the usage scenario. The method according to any one of claims 1 to 9, wherein, Before determining the second color feature value of the optical-mechanical image region in the target image, the method further includes: Determine the position coordinates of the optical-mechanical image area in the reference image; wherein, the reference image is obtained by the camera after the projection device projects a preset feature image onto a third projection background; Based on the location coordinates, the optical-mechanical image area in the target image is determined. The method according to claim 10, wherein, Determining the position coordinates of the optomechanical image region in the reference image includes: Extract the first feature point from the preset feature image; Extract the second feature point in the reference image that corresponds to the first feature point; Determine the projection transformation matrix based on the first feature point and the second feature point; The coordinates of the boundary points of the preset feature image are determined based on the resolution of the projection device. Based on the projection transformation matrix, the coordinates of the boundary points of the preset feature image are projected and transformed to obtain the position coordinates of the optical-mechanical image area in the reference image. The method according to any one of claims 1 to 9, wherein, The projection device stores a calibration image in its memory. The calibration image is obtained by the projection device projecting a preset solid color image onto the first projection background and then taking a picture with the camera. The step of obtaining the first color feature value includes: The calibration image is retrieved from the memory. Determine the first color feature value of the optical-mechanical image region in the calibration image. The method according to any one of claims 1 to 9, wherein, The first color feature value is stored in the memory of the projection device; The step of obtaining the first color feature value includes: Retrieve the first color feature value from the memory. The method according to any one of claims 1 to 9, wherein, The determination of the second color feature value of the optical-mechanical image region in the target image includes: Based on a dynamic threshold, candidate pixels are selected in the optical-mechanical image region of the target image; wherein, the dynamic threshold is determined based on the chromaticity components of each pixel in the optical-mechanical image region; and the similarity between the color of each candidate pixel and the color of the preset pure color image is greater than a preset degree threshold. The second color feature value is determined based on each candidate pixel. The method according to claim 14, wherein, Determining the second color feature value based on each candidate pixel includes: The brightness value of each candidate pixel is determined, and the candidate pixels are sorted in descending order of brightness value to obtain a sorting result; Based on the sorting results, candidate pixels in the top preset percentage are selected as reference pixels; The second color feature value is determined based on each reference pixel. The method according to claim 15, wherein, Determining the second color feature value based on each reference pixel includes: The average value of the second red channel in the second color feature value is obtained by averaging the red channel values ​​of each reference pixel. The average value of the second green channel in the second color feature value is obtained by averaging the green channel values ​​of each reference pixel. The average value of the second blue channel in the second color feature value is obtained by averaging the blue channel values ​​of each reference pixel. or, The average value of the second red chromaticity component in the second color feature value is obtained by averaging the red chromaticity component values ​​of each reference pixel. The second color feature value is obtained by averaging the blue chromaticity component values ​​of each reference pixel. The average value of the blue chromaticity component. The method according to claim 14, wherein, The dynamic threshold includes: the dynamic threshold corresponding to the red chromaticity component in the target image and the dynamic threshold corresponding to the blue chromaticity component in the target image; The dynamic threshold corresponding to the red chromaticity component in the target image is determined based on the red chromaticity component of each pixel in the optical-mechanical image region of the target image; The dynamic threshold corresponding to the blue chromaticity component in the target image is determined based on the blue chromaticity component of each pixel in the optical-mechanical image region of the target image. The method according to claim 17, wherein, The dynamic thresholds corresponding to the red chromaticity component and the blue chromaticity component in the target image are determined in the following manner: The optical-mechanical image area of ​​the target image is divided into multiple sub-regions; Calculate the mean of the red chromaticity component and the mean of the blue chromaticity component for each of the sub-regions; Calculate the standard deviation of the red chromaticity component and the standard deviation of the blue chromaticity component for each of the sub-regions; Select sub-regions that meet preset filtering conditions from the multiple sub-regions as target sub-regions; wherein, the standard deviation of the red chromaticity component of the target sub-region is greater than or equal to a first preset threshold, and the standard deviation of the blue chromaticity component of the target sub-region is greater than or equal to a second preset threshold. The average of the red chromaticity components of all the target sub-regions is used to obtain a first average, and the average of the blue chromaticity components of all the target sub-regions is used to obtain a second average. The standard deviations of the red chromaticity components of all the target sub-regions are averaged to obtain the third mean, and the standard deviations of the blue chromaticity components of all the target sub-regions are averaged to obtain the fourth mean. Based on the first mean and the third mean, determine the dynamic threshold corresponding to the red chromaticity component in the target image; Based on the second mean and the fourth mean, a dynamic threshold corresponding to the blue chromaticity component in the target image is determined. The method according to any one of claims 1 to 9, wherein, The preset solid color image is a pure white image, and the first projection background is a pure white projection background. A projection control device, wherein, Applied to a projection device, the projection device having a built-in camera, the projection control device includes: The first acquisition module is used to acquire a first color feature value; wherein the first color feature value is obtained by projecting a preset solid color image onto a first projection background by the projection device; the first projection background is located in the calibration scene of the projection device. A determining module is used to determine a second color feature value of the optical-mechanical image area in the target image; wherein, the target image is obtained by the camera after the preset solid color image is projected onto a second projection background by the projection device; the second projection background is located in the usage scenario of the projection device; The second acquisition module is used to acquire the ratio obtained based on the first color feature value and the second color feature value; The color gain determination module is used to determine the target color gain of the projection device in the usage scenario based on the ratio and the brightness loss; wherein the brightness loss is determined based on the ratio or based on the projection display brightness of the projection device, and the projection display brightness is the display brightness of the image projected by the projection device onto the second projection background. A projection device, wherein, The projection device includes: Memory, used to store executable program code; A processor for calling and running the executable program code from the memory, causing the projection device to perform the method as described in any one of claims 1 to 19. A computer-readable storage medium, wherein, The computer-readable storage medium stores a computer program that, when executed, implements the method as described in any one of claims 1 to 19.

Images