Color temperature correction system, color temperature correction method and non-transitory computer readable storage medium

Abstract

The invention provides a color temperature correction system, a color temperature correction method and a non-transitory computer readable storage medium. The system comprises a projector and an electronic device. In response to the color temperature correction instruction, an image acquisition module on the electronic device is enabled, and the projector projects a light beam to form a corrected image on a projection surface. The image capturing module is used for capturing an image towards the projection surface and generating an environment image. The processor obtains an area image corresponding to the correction image in the environment image. According to the area image and a plurality of image capturing parameters when the image capturing module captures the environment image, the processor calculates a color temperature estimation value and transmits the color temperature estimation value to the projector, and projection parameters are adjusted according to the projector. Therefore, the electronic device can assist the projector in color temperature correction.

Description

Technical Field

[0001] This disclosure relates to a color temperature correction system, a color temperature correction method, and a non-transitory computer-readable storage medium that can utilize electronic devices to assist a projector in color temperature correction. Background Technology

[0002] Traditional projectors typically offer only basic display options, such as adjusting parameters like brightness, contrast, and color saturation via on-screen display (OSD) menus. However, these adjustments often rely on the user's subjective judgment and do not take into account the impact of ambient light on projected image quality. Especially under varying ambient color temperatures, projectors may fail to provide optimal display performance because most projectors lack built-in sensors to automatically sense and adjust the color temperature of the projected image. Users must rely on their eyes to judge the ambient light's color temperature, which is not only easily influenced by environmental factors and personal preferences but can also lead to inaccurate adjustments.

[0003] The "Background Art" paragraph is only used to help understand the content of this invention. Therefore, the content disclosed in the "Background Art" paragraph may include some known technologies that are not known to those skilled in the art. The content disclosed in the "Background Art" paragraph does not mean that the content or the problems to be solved by one or more embodiments of this invention were known or understood by those skilled in the art prior to this application. Summary of the Invention

[0004] This invention proposes a color temperature correction system, a color temperature correction method, and a non-transitory computer-readable storage medium, which can detect color temperature through electronic devices and automatically adjust the projection parameters of the projector.

[0005] Other objects and advantages of the present invention can be further understood from the technical features disclosed herein.

[0006] To achieve one, some, or all of the above objectives, or other objectives, embodiments of the present invention provide a color temperature correction system comprising a projector and an electronic device connected in communication. The electronic device includes a processor and an image capturing module connected in communication. In response to the electronic device generating a color temperature correction command based on its operation, the processor enables the image capturing module and transmits a projection command corresponding to the corrected image to the projector. The projector projects a beam of the corrected image according to the projection command to form a corrected image on a projection surface. The image capturing module is used to capture an image onto the projection surface and generate an ambient image. The processor obtains a region image in the ambient image based on the ambient image, wherein the region image corresponds to at least a portion of the corrected image. Based on the region image in the ambient image and multiple image capturing parameters of the image capturing module when capturing the ambient image, the processor calculates a color temperature estimate and transmits the color temperature estimate to the projector. The projector adjusts its projection parameters based on the color temperature estimate.

[0007] Embodiments of the present invention also propose a color temperature correction method, comprising: responding to a color temperature correction command generated according to an operation, enabling an image capturing module, and transmitting a projection command corresponding to the correction image to a projector, causing the projector to project a correction image beam according to the projection command to form a correction image on a projection surface; obtaining a region image in an environmental image based on an environmental image, wherein the environmental image is generated by the image capturing module capturing an image toward the projection surface, and the region image corresponds to at least a portion of the correction image; and calculating a color temperature estimate based on the region image in the environmental image and multiple image capturing parameters of the image capturing module when capturing the environmental image, and transmitting the color temperature estimate to the projector, so that the projector adjusts its projection parameters according to the color temperature estimate.

[0008] Embodiments of the present invention also propose a non-transitory computer-readable storage medium for storing an application program that can be executed by a processor. When the application program is executed by the processor, it is used to perform the above-described color temperature correction method.

[0009] To make the above features and advantages of the present invention more apparent and understandable, specific embodiments are described below in conjunction with the accompanying drawings. Attached Figure Description

[0010] Figure 1 This is a schematic diagram illustrating a color temperature correction system according to one embodiment.

[0011] Figure 2 This is a flowchart illustrating the operation of a color temperature correction system according to an embodiment.

[0012] Figure 3 This is a schematic diagram illustrating the capture of a correction image according to one embodiment.

[0013] Figure 4 This is a schematic diagram illustrating experimental results according to one embodiment.

[0014] Figure 5 This is a flowchart illustrating a color temperature correction method according to an embodiment. Detailed Implementation

[0015] Some embodiments of the present invention will now be described in detail with reference to the accompanying drawings. Component symbols used in the following description are considered identical or similar when they appear in different drawings. These embodiments are only a part of the present invention and do not disclose all possible implementations of the invention. More precisely, these embodiments are merely examples of the systems and methods described in the claims of the present invention.

[0016] The foregoing descriptions and other technical contents, features, and effects of this invention will be clearly presented in the following detailed description of a preferred embodiment with reference to the accompanying drawings. The directional terms used in the following embodiments, such as up, down, left, right, front, or back, are merely for reference to the accompanying drawings. Therefore, the directional terms used are for illustrative purposes and not for limiting the invention.

[0017] Figure 1 This is a schematic diagram illustrating a color temperature correction system according to one embodiment. Please refer to... Figure 1 The color temperature correction system includes an electronic device 110 and a projector 120, which are interconnected. The electronic device 110 can be a smartphone, laptop, tablet, personal digital assistant, etc.

[0018] Electronic device 110 includes a processor 111, an image capturing module 112, a communication module 113, an input module 114, and a memory 115. The processor 111 is coupled to the image capturing module 112, the communication module 113, the input module 114, and the memory 115. The processor 111 may be a central processing unit, microprocessor, microcontroller, application-specific integrated circuit (ASIC), programmable logic device (PLD), etc. The image capturing module 112 may include a lens, aperture, shutter, light sensor, etc. The light sensor may be a charge-coupled device (CCD) sensor, a complementary metal-oxide-semiconductor (CMOS) sensor, or other suitable photosensitive element. The communication module 113 may include circuitry supporting communication functions such as near-field communication, infrared communication, Bluetooth, or Wi-Fi. The input module 114 may include a touchscreen, keyboard, or mouse, etc. The memory 115 may include RAM, flash memory, read-only memory, etc., in which application programs are stored and executed by the processor 111.

[0019] Projector 120 includes a projection module 121, a display processor 122, and a communication module 123. The display processor 122 is coupled to the projection module 121 and the communication module 123. The projection module 121 projects images onto a projection surface and may include a Digital Micromirror Device (DMD), a Liquid Crystal Display (LCD), a Liquid Crystal on Silicon (LCoS) panel, a Digital Light Processing (DLP) unit, a light source, a zoom lens, a zoom motor, or other display-related components. The display processor 122 may be, for example, a microprocessor, a display chip, a microcontroller, an application-specific integrated circuit, or a programmable logic device. The communication module 123 may include circuitry supporting near-field communication, infrared communication, Bluetooth, or Wi-Fi communication functions, used for communication with the communication module 113 of electronic device 110.

[0020] Projector 120 projects a correction image beam 130 onto projection surface 140 to form a correction image, while image capture module 112 of electronic device 110 captures an image toward projection surface 140 via user operation to obtain an environmental image. Based on this environmental image and other information acquired during image capture, electronic device 110 can assist projector 120 in performing color temperature correction.

[0021] Figure 2 This is a flowchart illustrating the operation of a color temperature correction system according to one embodiment. Please refer to... Figure 1 and Figure 2 First, user 210 operates 220 on electronic device 110, causing electronic device 110 to execute step 201: generating a color temperature correction command based on user 210's operation 220. In some embodiments, processor 111 executes an application program stored in memory 115. This application program provides an interface that may include one or more graphical objects, such as buttons, menus, sliders, etc. User 210 can operate 220 on this interface, for example, pressing a button corresponding to activate the color temperature correction function. The application program then causes processor 111 to generate a color temperature correction command based on this operation 220. The color temperature correction command enables electronic device 110 to enter the mode of automatically adjusting the color temperature of projector 120.

[0022] In response to the electronic device 110 generating a color temperature correction command based on the user 210's operation 220, in step 202, the processor 111 enables the image capturing module 112 and transmits a projection command 230 corresponding to the corrected image to the projector 120. The projection command 230 instructs the projector 120 to project a correction image beam corresponding to the corrected image. In some embodiments, the processor 111 can select one from multiple preset images as the corrected image to be presented on the projection surface, and then transmit the projection command 230 corresponding to this corrected image to the projector 120. In other embodiments, multiple options corresponding to multiple preset images can also be provided on the application executed by the processor 111, allowing the user 210 to select the corrected image to be presented on the projection surface, and then the processor 111 generates a projection command 230 corresponding to the selected corrected image to the projector 120. Since the processor 111 knows which preset image the corrected image is, it can also obtain relevant information about this corrected image, such as the grayscale of each color channel, the size of the image, etc.

[0023] In step 203, the projector 120 receives a projection instruction 230 and projects a correction image beam 130 according to the projection instruction 230 to form a correction image on the projection surface 140. This correction image can be a solid color image or an image with various patterns; the present invention does not limit the content of the correction image.

[0024] Next, the user 210 operates 220 on the electronic device 110, for example, by holding the electronic device 110 and taking a picture of the calibration image. Figure 3 This is a schematic diagram illustrating the capture of a corrected image according to one embodiment. Please refer to... Figure 2 and Figure 3 Projector 120 projects a correction image beam 130 to form a correction image 310 on projection surface 140. In some embodiments, an application running on electronic device 110 prompts user 210 to take a picture and marks a range 320 in the preview screen of electronic device 110, prompting user 210 to adjust the angle, position, or focus of electronic device 110 so that the correction image 310 in the preview screen falls within this range 320, and preferably the correction image 310 in the preview screen completely covers the entire range 320. In some embodiments, electronic device 110 may also set a threshold value for the percentage of the coverage area 320 of the correction image 310 in the preview screen, such as 75%, 85%, or 95%. If the percentage of the coverage area 320 of the correction image 310 in the preview screen does not reach the threshold value, user 210 is continuously reminded to make adjustments. A picture can only be taken when the percentage of the coverage area 320 of the correction image 310 in the preview screen exceeds the threshold value.

[0025] In response to user 210's operation 220 of taking a picture of the calibration image 310 with electronic device 110, in step 204, image capturing module 112 captures an image of the projection surface 140 and generates an environmental image. Furthermore, processor 111 obtains a region image from the environmental image. For example, processor 111 can capture pixels within range 320 as a region image. In some embodiments, if the calibration image 310 contains specific patterns or markings, such as a QR code around the calibration image 310, processor 111 can also identify the patterns or markings in the environmental image and then obtain a region image from the corresponding location. Through this process, the region image corresponds to at least a portion of the calibration image 310. In this embodiment, to measure the ambient color temperature, since the image captured by image capturing module 112 is formed by adding environmental factors to the calibration image, and the information of the calibration image is known in advance, the color temperature information about the environment can be calculated by capturing the calibration image (region image).

[0026] In step 205, the processor 111 calculates an estimated color temperature based on the area image and multiple image capture parameters of the image capturing module 112 when capturing the environmental image. These image capture parameters refer to parameters of the image capturing module 112 regarding the lens, image sensor, or algorithm, rather than parameters of the environmental image. These multiple image capture parameters are determined by the image capturing module 112 based on the environment when capturing the image. For example, image capture parameters may include shutter speed, aperture size, ISO, white balance parameters, and exposure compensation parameters. Shutter speed (i.e., exposure time) refers to the length of time from when the shutter of the image capturing module 112 opens to when it closes, during which time light is projected onto the image sensor through the lens of the image capturing module 112. The length of the exposure time directly affects the amount of light, thus affecting the brightness, color saturation, and motion capture effect of the image. The aperture size determines the amount of light entering the image capturing module 112. A larger aperture (smaller numerical value) allows more light in, resulting in a more pronounced background blur (shallow depth of field); a smaller aperture (larger numerical value) allows less light in, resulting in a deeper depth of field. Furthermore, higher ISO sensitivity leads to more noise in the image, potentially affecting color purity. White balance parameters refer to the parameters used by the processor 111 when executing the white balance algorithm. The main function of the white balance algorithm is to adjust the colors in the image to make them appear more natural or closer to the colors seen by the human eye. Different white balance parameters can produce different colors. Exposure compensation parameters are used to adjust the brightness of the image, and may include, but are not limited to, the exposure value (EV). In other embodiments, the image capturing parameters may also include parameters related to high dynamic range algorithms, contrast enhancement algorithms, noise reduction algorithms, gamma correction algorithms, etc., all of which affect the grayscale values ​​of pixels.

[0027] The image capturing module 112 has its own mechanism to determine imaging parameters such as shutter speed, aperture size, and ISO. For example, when the ambient light is low, it can reduce the shutter speed, increase the aperture size (by decreasing the value), and increase the ISO. These imaging parameters can reflect the environmental conditions. Generally, the image capturing module 112 is affected by the environment when capturing images, and the resulting environmental images will vary depending on environmental factors. Simultaneously, the environmental images will also differ due to the adjustment mechanism of the image capturing module 112 itself. For example, the specifications of the image capturing module 112 on different electronic devices 110 are different, and the image capturing module 112 may apply different image correction or color adjustment algorithms to process pixels. If only the pixels in the image are used for color temperature analysis, it may not accurately represent the color temperature of the actual environment. In this embodiment, the environmental color temperature (i.e., the estimated color temperature value) is calculated based on the area image in the environmental image and the imaging parameters, which can yield an environmental color temperature that more closely matches the actual situation.

[0028] In some embodiments, the processor 111 of the electronic device 110 transmits the aforementioned image acquisition parameters and region image to a machine learning model to obtain multiple first primary color values ​​from the machine learning model. This machine learning model may be, for example, a large language model, decision tree, random forest, k-nearest neighbor algorithm, multi-layer neural network, convolutional neural network, support vector machine, extreme gradient boosting (XGBoost), autoencoder, etc., and the present invention is not limited thereto. The architecture of the convolutional neural network may employ LeNet, AlexNet, VGG, GoogLeNet, ResNet, DenseNet, or YOLO (YouOnly Look Once), etc. When training the machine learning model, the labels of the training data can be generated through measurements using a colorimeter. The aforementioned machine learning model may be stored in the electronic device 110 (e.g., memory 115), or it may be set up on a server in the cloud, and the present invention is not limited thereto. In some embodiments, the aforementioned multiple first primary color values ​​correspond to different multiple color channels, such as red, green, and blue color channels. The processor 111 uses a machine learning model to calculate the three primary color values ​​corresponding to the color temperature based on the captured area image and the image capture parameters.

[0029] On the other hand, the processor 111 also calculates multiple second primary color values ​​based on the region image. For example, the processor 111 can average the grayscale values ​​of all pixels in the region image to calculate multiple second primary color values. In some embodiments, the processor 111 can also execute any image processing algorithm to calculate multiple second primary color values ​​based on principles such as the Gray World Assumption and the Perfect Reflector Assumption. In some embodiments, these second primary color values ​​also correspond to different color channels, such as the red, green, and blue color channels.

[0030] Next, a color temperature estimate can be calculated based on the aforementioned multiple primary color values ​​and multiple secondary color values. For example, for each color channel, the processor 111 can perform a weighted sum of the corresponding primary color value and the corresponding secondary color value to obtain the corresponding color estimate. In other words, three color channels will produce three color estimates, and these calculations are shown in the following mathematical formula 1.

[0031] [Mathematical Expression 1]

[0032] R e =w1×R Im +w2×R AI

[0033] G e =w1×G Im +w2×G AI

[0034] B e =(w1×B Im +w2×B AI )×α

[0035] Where R e This is the color estimate corresponding to the red channel, G. e This is the estimated color value corresponding to the green channel, B. e This is the color estimate corresponding to the blue channel. R Im It corresponds to the second primary color value of the red channel, G. Im It corresponds to the second primary color value of the green channel, B. Im It corresponds to the second primary color value in the blue channel. R AI It corresponds to the first primary color value of the red channel, G. AI It corresponds to the first primary color value of the green channel, B. AIThis corresponds to the first primary color value of the blue channel. w1 and w2 are weights, where w1 + w2 = 1, for example, w1 = 0.4 and w2 = 0.6. α is an adjustment parameter, for example, 0.92. In some embodiments, α can also be 1, and is not limited to this.

[0036] In the above embodiments, multiple color estimates are calculated by combining the calculation results of the machine learning model and the calculation results of the image processing based on the regional image. However, in other embodiments, information from the corrected image itself can also be added. Specifically, the processor 111 stores multiple third primary color values ​​(or multiple three primary color values ​​in the image data corresponding to the corrected image) in the image data corresponding to the corrected image. For example, the corrected image is a solid color image in which all pixels have the same grayscale value, and these grayscale values ​​can be used as third primary color values. In some embodiments, these third primary color values ​​also correspond to different color channels, such as red, green, and blue color channels. For each color channel, the processor 111 performs a weighted sum on the corresponding first primary color value, the corresponding second primary color value, and the corresponding third primary color value to obtain the corresponding color estimate, which can be expressed as the following mathematical formula 2.

[0037] [Mathematical Expression 2]

[0038] R e =w1×R Im +w2×R AI +w3×R c

[0039] G e =w1×G Im +w2×G AI +w3×G c

[0040] B e =(w1×B Im +w2×B AI +w3×B c )×α

[0041] Where R c G corresponds to the third primary color value in the red channel. c B corresponds to the third primary color value in the green channel. cThis corresponds to the third primary color value of the blue channel. w3 is the weight; in this example, w1 + w2 + w3 = 1, for example, w1 = 0.35, w2 = 0.5, w3 = 0.15. Furthermore, in this example, α = 0.92. The reason for designing the adjustment parameter α is that, in some cases, the lens of the image capturing module 112 is more sensitive to blue, and multiplying the primary color value of the blue channel by the adjustment parameter α can obtain a more accurate color temperature. In some embodiments, α can also be 1, and is not limited to this.

[0042] Regardless of whether Formula 1 or Formula 2 is used, the processor 111 can calculate the color temperature estimate based on multiple color estimates. Generally, higher color temperatures tend to lean towards red, while lower color temperatures tend to lean towards blue. Based on the three color estimates, their approximate colors can be evaluated, and thus the color temperature estimate can be calculated. In some embodiments, the processor 111 can calculate the ratio between the color estimate corresponding to the blue channel and the sum of all color estimates, expressed as Formula 3 below.

[0043] [Mathematical Expression 3]

[0044]

[0045] Next, the estimated color temperature value can be obtained based on the ratio calculated using Formula 3. For example, the higher the ratio calculated by Formula 3, the lower the estimated color value; conversely, the lower the ratio, the higher the estimated color value. In some embodiments, the unit of the estimated color temperature value may be... o K, but in other embodiments, the color temperature estimate can also be a value at any scale to represent the level of color temperature. The processor 111 substitutes the above proportion into any function to calculate the color temperature estimate. This function can include linear functions, polynomial functions, exponential functions, etc., and the present invention is not limited thereto.

[0046] In some embodiments, the ratio calculated according to Mathematical Formula 3 and the look-up table can obtain a color temperature estimation value. For example, the look-up table can be established in advance. In the experimental data, the true color temperature estimation value can be obtained through a colorimeter, and then these true color temperature estimation values and the corresponding ratios are written into the look-up table. The processor 111 can input the ratio calculated according to Mathematical Formula 3 into the look-up table to obtain the color temperature estimation value. Since the look-up table only has a limited number of ratios, if the calculated ratio is not exactly the same as the ratio in the look-up table, after the ratio is input into the look-up table, the two closest color temperature estimation values will be obtained. These two color temperature estimation values can form an approximate color temperature range, and then the color temperature estimation value can be calculated according to this approximate color temperature range using the linear interpolation method. For example, currently the calculated ratio is Rt, and the values in the look-up table closest to the ratio Rt are ratio R1 and ratio R2, where R1 < R2. Ratio R1 corresponds to the color temperature estimation value K1 in the look-up table, and ratio R2 corresponds to the color temperature estimation value K2 in the look-up table. Therefore, the processor 111 can obtain the approximate color temperature range K1~K2 according to ratio R1 and ratio R2, and calculate the color temperature estimation value Kt using the linear interpolation method. The detailed calculation can be expressed as the following Mathematical Formula 4.

[0047] [Mathematical Formula 4]

[0048]

[0049] Please refer to Figure 2 , next, the processor 111 of the electronic device 110 will transmit the calculated color temperature estimation value 240 to the projector 120 through the communication module 113. In step 206, the projector 120 adjusts the projection parameters of the projector 120 according to the color temperature estimation value 240. This projection parameter can include the color temperature or the amplification of a certain color channel, etc., which is not limited herein. Since the color temperature estimation value 240 represents the color temperature of the corrected image, in some embodiments, the display processor 122 in the projector 120 can further compare the color temperature estimation value 240 with the color of the corrected image, and then determine how to adjust the projection parameters.

[0050] Figure 4 is a schematic diagram showing experimental results according to an embodiment. Please refer to Figure 4 , where the horizontal axis is the test number, and different test numbers represent different corrected images or different environments, and the vertical axis is the color temperature (or color temperature estimation value). Figure 4 shows curves 401~404, where curve 401 represents the true color temperature measured by the colorimeter; curve 402 represents the color temperature estimation value calculated only based on the regional image; curve 403 represents the color temperature estimation value calculated only using the machine learning algorithm; curve 404 represents the color temperature estimation value calculated using the above Mathematical Formula 2 and the corresponding weighted average. From Figure 4It can be seen that the trends of curve 404 and curve 401 are similar, which means that the method of combining multiple information and then weighting the average can calculate a color temperature that is more in line with the actual situation.

[0051] Figure 5 This is a flowchart illustrating a color temperature correction method according to an embodiment. Please refer to... Figure 5 In step 501, in response to a color temperature correction command generated according to the operation, the image capturing module is enabled, and a projection command corresponding to the corrected image is transmitted to the projector, causing the projector to project a beam of the corrected image according to the projection command to form a corrected image on the projection surface. In step 502, a region image in the environmental image is obtained based on the environmental image, wherein the environmental image is generated by the image capturing module capturing an image onto the projection surface, and the region image corresponds to at least a portion of the corrected image. In step 503, a color temperature estimate is calculated based on the region image in the environmental image and the image capturing parameters of the image capturing module when capturing the environmental image, and the color temperature estimate is transmitted to the projector, so that the projector adjusts its projection parameters according to the color temperature estimate. Figure 5 Each step has been explained in detail above and will not be repeated here. It is worth noting that... Figure 5 Each step can be implemented as multiple program codes or circuits, but the present invention is not limited thereto. Furthermore, Figure 5 The method can be used in conjunction with the above embodiments or alone; in other words, Figure 5 Other steps can also be added between the various steps.

[0052] This invention also proposes a non-transitory computer-readable storage medium, such as random access memory, read-only memory, flash memory, floppy disk, hard disk, optical disk, USB flash drive, magnetic tape, etc. This non-transitory computer-readable storage medium stores an application program that can be executed by a processor. When executed by the processor, this application program is used to perform the aforementioned color temperature correction method.

[0053] In summary, the color temperature correction system and method of the present invention have at least one of the following advantages. First, using an electronic device to assist in color temperature correction solves the problem of projectors lacking sensors. Second, the above embodiments additionally use image acquisition parameters instead of only using image pixels to calculate color temperature, avoiding the influence of various algorithms on the electronic device. Third, using a weighted average to calculate the estimated color temperature value can combine the advantages of various methods to obtain data closer to reality. Through the above means, the user experience can be improved, image quality performance can be enhanced, and the time for color temperature correction can be reduced using electronic devices.

[0054] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Any simple equivalent changes and modifications made in accordance with the claims and description of the invention are still within the scope of this patent. Furthermore, no embodiment or claim of the present invention needs to achieve all the objectives, advantages, or features disclosed in the invention. In addition, the abstract and title (invention title) are only used to assist in patent document retrieval and are not intended to limit the scope of the invention. Moreover, the terms "first," "second," etc., mentioned in this specification or claims are only used to name elements or distinguish different embodiments or scopes, and are not used to limit the upper or lower limit of the number of elements.

Claims

1. A color temperature correction system, characterized by, The color temperature correction system comprises a projector and an electronic device connected via communication, The electronic device comprises a processor and an image capturing module connected via communication, In response to the electronic device generating a color temperature correction instruction according to operation, the processor enables the image capturing module and transmits a projection instruction corresponding to a correction image to the projector, and the projector projects a correction image light beam according to the projection instruction to form the correction image on a projection surface, The image capturing module is used to capture an environment image toward the projection surface, The processor obtains a region image in the environment image according to the environment image, wherein the region image corresponds to at least part of the correction image, According to the region image in the environment image and a plurality of image capturing parameters of the image capturing module when capturing the environment image, the processor calculates a color temperature estimation value and transmits the color temperature estimation value to the projector, The projector adjusts at least one projection parameter of the projector according to the color temperature estimation value.

2. The color temperature correction system of claim 1, wherein, The plurality of image capturing parameters comprises at least one of shutter speed, aperture size, sensitivity, white balance parameter and exposure compensation parameter.

3. The color temperature correction system of claim 2, wherein, The processor is used to transfer the plurality of image capturing parameters and the region image in the environment image to a machine learning model to obtain a plurality of first primary color values from the machine learning model, The processor calculates a plurality of second primary color values according to the region image in the environment image, and calculates the color temperature estimation value according to the plurality of first primary color values and the plurality of second primary color values.

4. The color temperature correction system of claim 3, wherein The plurality of first primary color values respectively correspond to different color channels, and the plurality of second primary color values respectively correspond to different color channels, For each of the plurality of color channels, the processor is used to perform a weighted sum of the corresponding first primary color value and the corresponding second primary color value to obtain a corresponding color estimation value, The processor calculates the color temperature estimation value according to the plurality of color estimation values.

5. The color temperature correction system of claim 4, wherein, The plurality of color channels comprises a red channel, a green channel and a blue channel, and the processor is used to calculate the ratio between the color estimation value corresponding to the blue channel and the sum of the plurality of color estimation values, and obtain the color temperature estimation value according to the ratio.

6. The color temperature correction system of claim 3, wherein, The processor stores a plurality of third primary color values in the image data corresponding to the correction image, the plurality of first primary color values respectively correspond to different color channels, the plurality of second primary color values respectively correspond to different color channels, and the plurality of third primary color values respectively correspond to different color channels, For each of the plurality of color channels, the processor is used to perform a weighted sum of the corresponding first primary color value, the corresponding second primary color value and the corresponding third primary color value to obtain a corresponding color estimation value, The processor calculates the color temperature estimation value according to the plurality of color estimation values.

7. The color temperature correction system of claim 6, wherein, The multiple color channels include a red channel, a green channel, and a blue channel, and the processor is configured to calculate a ratio between the color estimation value corresponding to the blue channel and a sum of the multiple color estimation values, and obtain the color temperature estimation value according to the ratio.

8. The color temperature correction system according to any one of claims 5 or 7, wherein The processor is configured to obtain the color temperature estimation value according to the ratio and a lookup table.

9. The color temperature correction system of claim 8, wherein, The processor is configured to obtain an approximate color temperature range according to the ratio and the lookup table, and calculate the color temperature estimation value using a linear difference method according to the approximate color temperature range.

10. The color temperature correction system of claim 1, wherein, The electronic device includes an application program, wherein when the processor executes the application program, the application program causes the processor to generate the color temperature correction instruction according to the operation.

11. A color temperature correction method, characterized by, The color temperature correction method includes: In response to generating a color temperature correction instruction according to an operation, enabling an image capturing module, and transmitting a projection instruction corresponding to a corrected image to a projector, the projector projects a corrected image light beam according to the projection instruction to form the corrected image on a projection surface; According to the environment image, obtain a region image in the environment image, wherein the environment image is generated by the image capturing module taking an image toward the projection surface, and the region image corresponds to at least part of the corrected image; and According to the region image in the environment image and multiple image taking parameters of the image capturing module when capturing the environment image, calculate a color temperature estimation value, and transmit the color temperature estimation value to the projector, so that the projector adjusts at least one projection parameter of the projector according to the color temperature estimation value.

12. The color temperature correction method according to claim 11, wherein The multiple image taking parameters include at least one of shutter speed, aperture size, sensitivity, white balance parameter, and exposure compensation parameter.

13. The color temperature correction method according to claim 12, wherein The color temperature correction method further includes: Transmit the multiple image taking parameters and the region image in the environment image to a machine learning model to obtain multiple first primary color values from the machine learning model; and According to the region image in the environment image, calculate multiple second primary color values, and according to the multiple first primary color values and the multiple second primary color values, calculate the color temperature estimation value.

14. The color temperature correction method according to claim 13, wherein The multiple first primary color values correspond to different multiple color channels respectively, and the multiple second primary color values correspond to different multiple color channels respectively, and the color temperature correction method further includes: For each of the multiple color channels, perform a weighted sum on the corresponding first primary color value and the corresponding second primary color value to obtain a corresponding color estimation value; and According to the multiple color estimation values, calculate the color temperature estimation value.

15. The color temperature correction method according to claim 14, wherein The multiple color channels include a red channel, a green channel, and a blue channel, and the color temperature correction method further includes: Calculate a ratio between the color estimation value corresponding to the blue channel and a sum of the multiple color estimation values, and obtain the color temperature estimation value according to the ratio.

16. The color temperature correction method according to claim 13, wherein The color temperature correction method further includes: accessing a plurality of third primary color values in image data corresponding to the corrected image, wherein the plurality of first primary color values respectively correspond to different color channels, the plurality of second primary color values respectively correspond to different color channels, and the plurality of third primary color values respectively correspond to different color channels; for each of the color channels, performing a weighted sum on the corresponding first primary color value, the corresponding second primary color value, and the corresponding third primary color value to obtain a corresponding color estimate value; and calculating the color temperature estimate value according to the plurality of color estimate values.

17. The color temperature correction method according to claim 16, wherein The color channels include a red channel, a green channel, and a blue channel, and the color temperature correction method further comprises: calculating a ratio between the color estimate value corresponding to the blue channel and a sum of the plurality of color estimate values, and obtaining the color temperature estimate value according to the ratio.

18. The color temperature correction method according to claim 17, wherein The color temperature correction method further comprises: obtaining the color temperature estimate value according to the ratio and a lookup table.

19. The color temperature correction method according to claim 18, wherein The color temperature correction method further comprises: obtaining an approximate color temperature range according to the ratio and the lookup table, and calculating the color temperature estimate value using a linear difference method according to the approximate color temperature range.

20. A non-transitory computer-readable storage medium, comprising: The non-transitory computer-readable storage medium stores an application program executable by a processor, and the application program, when executed by the processor, is used to complete the color temperature correction method according to any one of claims 11-19.

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