Image rendering method, display device, and storage medium

Abstract

The application discloses an image rendering method, a display device and a storage medium. The method comprises the following steps: acquiring a target image frame, and dividing the target image frame into multiple image regions; determining uniformity analysis results corresponding to the image regions according to the gray values of pixels in the image regions; determining a rendering resolution according to multiple uniformity analysis results corresponding to the multiple image regions; and rendering the target image frame according to the rendering resolution. The application aims to reduce energy consumption while ensuring display effect in the image rendering process.

Description

Technical Field

[0001] This invention relates to the field of display device technology, and more particularly to image rendering methods, display devices, and storage media. Background Technology

[0002] When display devices (such as head-mounted displays) play videos or display single-frame images, the content they display can be complex, such as urban scenes, or simple, such as large areas of white walls or large areas of darkness.

[0003] However, currently, when display devices play videos or display single-frame images, regardless of whether the displayed content is simple or complex, they will render according to a pre-set fixed resolution. However, this can easily lead to problems such as wasted energy when the display content is simple and poor display effect when the rendering resolution is too low when the display content is complex. Summary of the Invention

[0004] The main objective of this invention is to provide an image rendering method, a display device, and a storage medium, which aim to reduce energy consumption while ensuring display quality.

[0005] To achieve the above objectives, the present invention provides an image rendering method, the image rendering method comprising the following steps:

[0006] Acquire the target image frame and divide the target image frame into multiple image regions;

[0007] The uniformity analysis result of the corresponding image region is determined based on the grayscale value of the pixels in the image region;

[0008] The rendering resolution is determined based on the multiple uniformity analysis results corresponding to the multiple image regions;

[0009] The target image frame is rendered according to the rendering resolution.

[0010] Optionally, the uniformity analysis result includes whether the sub-images within the image region are uniform, and the step of determining the uniformity analysis result corresponding to the image region based on the grayscale values ​​of the pixels in the image region includes:

[0011] Determine the first mean and first standard deviation of all gray values ​​corresponding to all pixels in the image region;

[0012] The first grayscale range is determined based on the first mean and the first standard deviation;

[0013] Whether the corresponding sub-image is uniform is determined based on the grayscale value of the pixels in the image region and the first grayscale range.

[0014] Optionally, the step of determining whether the corresponding sub-image is uniform based on the grayscale values ​​of pixels in the image region and the first grayscale range includes:

[0015] Determine a first statistical number of target pixels in the image region, wherein the gray value corresponding to the target pixel is located within the first gray range;

[0016] Whether the corresponding sub-image is uniform is determined based on the first statistical count.

[0017] Optionally, the step of determining whether the corresponding sub-image is uniform based on the first statistical quantity includes:

[0018] Determine the first percentage of the first statistical quantity in the total number of pixels in the corresponding image region;

[0019] When the first proportion is greater than or equal to the first preset proportion, the corresponding sub-image is determined to be uniform;

[0020] When the first proportion is less than the first preset proportion, it is determined that the corresponding sub-image is uneven.

[0021] Optionally, the uniformity analysis result includes whether the sub-images within the image region are uniform, and the step of determining the rendering resolution based on the multiple uniformity analysis results corresponding to the multiple image regions includes:

[0022] A second statistical quantity of target image regions is determined among the plurality of image regions, and the uniformity analysis result of the target image regions is the uniformity of the corresponding sub-images;

[0023] The rendering resolution is determined based on the second statistical quantity.

[0024] Optionally, the step of determining the rendering resolution based on the second statistical quantity includes:

[0025] Determine the second percentage of the second statistical quantity in the total number of the plurality of image regions;

[0026] When the second proportion is greater than or equal to the second preset proportion, the first rendering resolution is determined to be the rendering resolution;

[0027] When the second proportion is less than the second preset proportion, the second rendering resolution is determined to be the rendering resolution;

[0028] Wherein, the first rendering resolution is less than the second rendering resolution.

[0029] Optionally, before the step of determining the first rendering resolution as the rendering resolution when the second proportion is greater than or equal to the second preset proportion, the method further includes:

[0030] The resolution adjustment value is determined based on the grayscale values ​​of pixels in the multiple image regions;

[0031] The second rendering resolution is reduced according to the resolution adjustment value to obtain the first rendering resolution.

[0032] Optionally, the step of determining the resolution adjustment value based on the grayscale values ​​of pixels in the plurality of image regions includes:

[0033] A first mean value is determined for each of the image regions, wherein the first mean value is the mean value of all gray values ​​corresponding to all pixels in the image region;

[0034] The mean of all the first means is determined to be the second mean, and the standard deviation of all the first means is determined to be the second standard deviation;

[0035] The second grayscale range is determined based on the second mean and the second standard deviation;

[0036] The resolution adjustment value is determined based on the second mean and the second grayscale range.

[0037] Optionally, the step of determining the resolution adjustment value based on the second mean and the second grayscale range includes:

[0038] Determine the third statistical number of the second means that are located within the second grayscale interval among all the second means;

[0039] Determine the third percentage of the total number of the third statistical quantity relative to the second mean;

[0040] The resolution adjustment value is determined based on the third proportion, and the resolution adjustment value is positively correlated with the third proportion.

[0041] Optionally, before the step of determining the uniformity analysis result corresponding to the image region based on the grayscale values ​​of pixels in the image region, the method further includes:

[0042] Based on the color values ​​corresponding to the pixel in multiple preset color channels;

[0043] The grayscale value of the pixel is obtained by weighting the color value of the pixel according to the weight value corresponding to each preset color channel.

[0044] In addition, to achieve the above objectives, this application also proposes a display device, the display device comprising: a memory, a processor, and an image rendering program stored in the memory and executable on the processor, wherein the image rendering program, when executed by the processor, implements the steps of the image rendering method as described in any of the preceding claims.

[0045] In addition, to achieve the above objectives, this application also proposes a storage medium storing an image rendering program, which, when executed by a processor, implements the steps of the image rendering method as described in any of the preceding claims.

[0046] This invention proposes an image rendering method that divides the target image frame to be displayed into multiple image regions. Based on the grayscale values ​​of pixels in each image region, a uniformity analysis result is determined. The rendering resolution is then determined based on the uniformity analysis results of the multiple image regions to render the target image frame. The uniformity analysis results of the multiple image regions accurately reflect the uniformity of the displayed content of the target image frame. By determining the rendering resolution of the target image frame according to the uniformity of the actual displayed content, the rendering resolution used for image frame rendering is no longer a pre-set fixed parameter but can be adjusted to adapt to the complexity of the actual image display content. This helps avoid rendering resolution being too high or too low, thereby ensuring display quality while reducing energy consumption. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the hardware structure involved in the operation of an embodiment of the display device of the present invention;

[0048] Figure 2 This is a schematic flowchart of an embodiment of the image rendering method of the present invention;

[0049] Figure 3 This is a schematic flowchart of another embodiment of the image rendering method of the present invention;

[0050] Figure 4 This is a flowchart illustrating another embodiment of the image rendering method of the present invention;

[0051] Figure 5 This is a flowchart illustrating another embodiment of the image rendering method of the present invention.

[0052] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0053] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0054] This invention provides a display device. In this embodiment, the display device is a head-mounted display device (e.g., a virtual reality device, an augmented reality device, etc.). In other embodiments, the display device may also be other types of devices with display functions, such as a television, a tablet computer, a mobile phone, etc.

[0055] In this embodiment of the invention, reference is made to Figure 1 The display device includes: a processor 1001 (e.g., CPU), a memory 1002, a timer 1003, etc. The components in the control device are connected via a communication bus. The memory 1002 can be high-speed RAM or stable memory (non-volatile memory), such as disk storage. Optionally, the memory 1002 can also be a storage device independent of the aforementioned processor 1001.

[0056] Those skilled in the art will understand that Figure 1 The device structure shown does not constitute a limitation on the device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0057] like Figure 1 As shown, the memory 1002, which serves as a storage medium, may include an image rendering program. Figure 1 In the apparatus shown, the processor 1001 can be used to call the image rendering program stored in the memory 1002 and execute the relevant steps of the image rendering method in the following embodiments.

[0058] This invention also provides an image rendering method applied to the aforementioned display device.

[0059] Reference Figure 2 This application proposes an embodiment of an image rendering method. In this embodiment, the image rendering method includes:

[0060] Step S10: Obtain the target image frame and divide the target image frame into multiple image regions;

[0061] The target image frame is specifically a single frame of image that the display device needs to display, or it can be a video frame in a video that the display device needs to display.

[0062] Each image region comprises multiple pixels, and the number of pixels in each image region may be the same or different. The number of multiple image regions can be a fixed number preset, or it can be determined according to the image type corresponding to the target image frame (e.g., landscape image or city image). Different image types may correspond to different numbers of image regions.

[0063] Step S20: Determine the uniformity analysis result of the corresponding image region based on the gray values ​​of the pixels in the image region;

[0064] Each image region corresponds to a uniformity analysis result. The uniformity analysis result characterizes the degree of uniformity or whether the sub-image is uniform at different locations within the corresponding image region.

[0065] Specifically, the mean grayscale value of all pixels in each image region or multiple pixels located at the target position in the image region can be determined, and the corresponding uniformity analysis result can be determined based on the deviation between the grayscale value of each pixel and the mean. And / or, the variance, standard deviation, etc., of all pixels in each image region or multiple pixels located at the target position in the image region can be determined, and the corresponding uniformity analysis result can be determined based on the variance and standard deviation.

[0066] Step S30: Determine the rendering resolution based on the multiple uniformity analysis results corresponding to the multiple image regions;

[0067] Specifically, the overall uniformity analysis result corresponding to the target image frame can be determined based on multiple uniformity analysis results, and the rendering resolution can be determined based on the overall uniformity analysis result.

[0068] In addition, the characterization value corresponding to each uniformity analysis result in multiple uniformity analysis results can be determined. Different results correspond to different characterization values, and the rendering resolution here is calculated based on multiple characterization values.

[0069] Step S40: Render the target image frame according to the rendering resolution.

[0070] This invention proposes an image rendering method that divides the target image frame to be displayed into multiple image regions. Based on the grayscale values ​​of pixels in each image region, a uniformity analysis result is determined. The rendering resolution is then determined based on the uniformity analysis results of the multiple image regions to render the target image frame. The uniformity analysis results of the multiple image regions accurately reflect the uniformity of the displayed content of the target image frame. By determining the rendering resolution of the target image frame according to the uniformity of the actual displayed content, the rendering resolution used for image frame rendering is no longer a pre-set fixed parameter but can be adjusted to adapt to the complexity of the actual image display content. This helps avoid rendering resolution being too high or too low, thereby ensuring display quality while reducing energy consumption.

[0071] Furthermore, based on the above embodiments, another embodiment of the image rendering method of this application is proposed. In this embodiment, reference is made to... Figure 3 Step S20 includes:

[0072] Step S21: Determine the first mean and first standard deviation of all gray values ​​corresponding to all pixels in the image region;

[0073] Each image region has a corresponding first mean and first standard deviation.

[0074] Step S22: Determine the corresponding first grayscale range based on the first mean and the first standard deviation;

[0075] The first grayscale interval represents the range of pixel grayscale values ​​allowed when the sub-images within the image region are uniform.

[0076] In this embodiment, an adjustment value is determined based on a first standard deviation. The first mean is then adjusted based on the adjustment value to obtain the interval thresholds (maximum and / or minimum thresholds) of the first grayscale interval. The range of grayscale values ​​defined by these interval thresholds is then used as the first grayscale interval. Specifically, after adjusting the first mean based on the adjustment value, the maximum and minimum thresholds of the first grayscale interval are obtained. The set of all grayscale values ​​between the maximum and minimum thresholds is then defined as the first grayscale interval.

[0077] Specifically, in this embodiment, a preset multiple of the first standard deviation (greater than 1, which can be an integer multiple or a non-integer multiple) is used as the adjustment value. In other embodiments, the first standard deviation can also be used directly as the adjustment value.

[0078] In this embodiment, the adjustment value is the adjustment range, the difference between the first mean and the adjustment range is taken as the minimum critical value of the first grayscale interval, and the sum of the first mean and the adjustment range is taken as the maximum critical value of the first grayscale interval.

[0079] For example, if the first mean is μ1 and the first standard deviation is σ1, then the first gray range is [μ1-3σ1, μ1+3σ1].

[0080] Step S23: Determine whether the corresponding sub-image is uniform based on the grayscale values ​​of the pixels in the image region and the first grayscale range.

[0081] Specifically, determine whether the gray value of each pixel in all pixels of the image region or multiple pixels at the target location are located within the corresponding first gray value interval, obtain multiple judgment results, and determine whether the corresponding sub-image is uniform based on the multiple judgment results.

[0082] In addition, the size or quantity relationship (e.g., difference) between the gray value of each pixel in all pixels in the image region or the gray value of multiple pixels corresponding to the target position and the critical value of the first gray range can be determined to obtain multiple recognition results. Based on the multiple recognition results, it can be determined whether the corresponding sub-image is uniform.

[0083] In this embodiment, by analyzing the mean and standard deviation of pixel grayscale values ​​in the image region, a first grayscale interval determined based on the mean and standard deviation is used to characterize the grayscale range when the image is uniform. Thus, the grayscale values ​​of pixels in the image region and the first grayscale interval can accurately determine whether the corresponding sub-image is uniform, which helps to improve the accuracy of the uniformity analysis results of each image region, thereby further improving the accuracy of the subsequently determined rendering resolution, and further ensuring the display effect while reducing energy consumption.

[0084] Furthermore, in this embodiment, step S23 includes: determining a first statistical number of target pixels in the image region, wherein the gray value corresponding to the target pixel is located within the first gray value range; and determining whether the corresponding sub-image is uniform based on the first statistical number.

[0085] Specifically, determine whether the gray value of each pixel in the image region is within the first gray range, obtain the judgment result corresponding to each pixel, and count the total number of judgment results that are "yes" among all judgment results as the first statistical quantity.

[0086] In this embodiment, a first percentage of the first statistical quantity in the total number of pixels in the corresponding image region is determined; when the first percentage is greater than or equal to a first preset percentage, the corresponding sub-image is determined to be uniform; when the first percentage is less than the first preset percentage, the corresponding sub-image is determined to be non-uniform. In this embodiment, the first preset percentage is greater than or equal to 65% and less than 100%, for example, the first preset percentage is 70%, 80%, 90%, etc. The first preset percentage can be a fixed parameter set in advance, a parameter determined by obtaining user-set parameters, or a parameter determined according to the display mode of the head-mounted display device (e.g., whether it is a perspective mode).

[0087] In other embodiments, the uniformity of the corresponding sub-image can be determined when the first statistical quantity is greater than or equal to a preset quantity; and the non-uniformity of the corresponding sub-image can be determined when the first statistical quantity is less than the preset quantity.

[0088] In this embodiment, the first statistical quantity accurately reflects the number of pixels with small differences in grayscale values ​​within an image region. A higher first statistical quantity indicates more pixels with small differences in grayscale values, suggesting a more uniform sub-image. Conversely, a lower first statistical quantity indicates more pixels with large differences in grayscale values, suggesting a less uniform sub-image. Therefore, the first statistical quantity accurately reflects the uniformity of sub-images within a corresponding image region, further improving the accuracy of the uniformity analysis results. Specifically, a first preset proportion is used as a threshold value to distinguish whether sub-images within an image region are uniform. By comparing the first proportion with the first preset proportion, the uniformity analysis results of the image region can be accurately determined.

[0089] Furthermore, based on any of the above embodiments, another embodiment of the image rendering method of this application is proposed. In this embodiment, the uniformity analysis result includes whether the sub-images within the image region are uniform, referring to... Figure 4 Step S30 includes:

[0090] Step S31: Determine the second statistical quantity of the target image region among the plurality of image regions, wherein the uniformity analysis result of the target image region is the uniformity of the corresponding sub-image;

[0091] Specifically, the total number of image regions whose uniformity analysis results correspond to uniform sub-images across all image regions is used as the second statistical quantity.

[0092] Step S32: Determine the rendering resolution based on the second statistical quantity.

[0093] Different second statistical values ​​correspond to different rendering resolutions, and the rendering resolution is negatively correlated with the second statistical value. Specifically, a correspondence between the second statistical value and the rendering resolution can be established in advance. This correspondence can include calculation relationships, mapping relationships, etc. Based on this correspondence, the rendering resolution corresponding to the current second statistical value can be determined.

[0094] Specifically, the range in which the second statistical quantity lies can be determined, and the preset rendering resolution associated with that range can be used as the rendering resolution. Alternatively, the rendering resolution can be calculated by substituting the second statistical quantity into a preset calculation formula.

[0095] In this embodiment, a second percentage of the second statistical quantity in the total number of the plurality of image regions is determined; when the second percentage is greater than or equal to a second preset percentage, a first rendering resolution is determined as the rendering resolution; when the second percentage is less than the second preset percentage, a second rendering resolution is determined as the rendering resolution; wherein, the first rendering resolution is less than the second rendering resolution.

[0096] In this embodiment, the second preset percentage is greater than or equal to 65% and less than 100%, for example, the second preset percentage is 70%, 80%, 90%, etc. The second preset percentage can be a fixed parameter set in advance, a parameter determined by obtaining user-set parameters, or a parameter determined according to the display mode of the head-mounted display device (e.g., whether it is a see-through mode).

[0097] The first rendering resolution and the second rendering resolution can be preset fixed values, or values ​​determined based on the actual image parameters of the target image frame. In this embodiment, the second rendering resolution is a preset fixed value, and the first rendering resolution is a parameter obtained by decreasing the second rendering resolution. In other embodiments, the first rendering resolution is a preset fixed value, and the second rendering resolution is a parameter obtained by increasing the first rendering resolution. In this embodiment, the second rendering resolution is 100%. In other embodiments, the second rendering resolution may also be less than 100%.

[0098] In other embodiments, the first rendering resolution may be determined as the rendering resolution when the second statistical quantity is greater than or equal to a preset quantity; and the second rendering resolution may be determined as the rendering resolution when the second statistical quantity is less than the preset quantity.

[0099] In this embodiment, the second statistical quantity accurately reflects the overall image uniformity of the target image frame. Determining the rendering resolution based on the second statistical quantity helps ensure that the image rendering process of the target image frame is precisely matched with the overall uniformity of the target image frame, thereby further guaranteeing the display quality of the target image frame while reducing energy consumption. The second preset percentage serves as a critical value for distinguishing whether the target image frame is uniform overall. The relationship between the second percentage and the second preset percentage accurately reflects the uniformity of the overall content of the target image frame, thereby further improving the accuracy of the subsequently determined rendering resolution.

[0100] Furthermore, based on any of the above embodiments, another embodiment of the image rendering method of this application is proposed. In this embodiment, reference is made to... Figure 5 Before the step of determining the first rendering resolution as the rendering resolution when the second proportion is greater than or equal to the second preset proportion, the method further includes:

[0101] Step S01: Determine the resolution adjustment value based on the grayscale values ​​of pixels in the plurality of image regions;

[0102] Specifically, grayscale feature values ​​(such as mean, maximum grayscale value, minimum grayscale value, or weighted average) corresponding to each image region can be determined based on the grayscale values ​​of pixels in each region. The resolution adjustment value is then determined based on multiple grayscale feature values. Specifically, the resolution adjustment value can be calculated by substituting multiple grayscale feature values ​​into a preset formula.

[0103] Alternatively, a first number of grayscale feature values ​​that meet preset conditions can be counted among multiple grayscale feature values, and the resolution adjustment value can be determined based on this first number. Specifically, the resolution adjustment value can be calculated by substituting the first number into a preset formula, or the relationship between the first number and a preset threshold can be determined, and the resolution adjustment value can be determined based on this relationship.

[0104] Alternatively, one can count the first number of grayscale feature values ​​that meet preset conditions and the second number of grayscale feature values ​​that do not meet preset conditions, and then determine the resolution adjustment value based on the first and second numbers. Specifically, one can determine the magnitude or quantitative relationship (e.g., difference or ratio) between the first and second numbers, and then determine the resolution adjustment value based on this magnitude or quantitative relationship.

[0105] Step S02: Decrease the second rendering resolution according to the resolution adjustment value to obtain the first rendering resolution.

[0106] The resolution adjustment value can be an adjustment range or an adjustment coefficient. For example, when the resolution adjustment value is an adjustment range, the difference between the second rendering resolution and the resolution adjustment value is used as the first rendering resolution.

[0107] In this embodiment, the resolution adjustment value is determined based on the grayscale values ​​of pixels in multiple image regions. The first rendering resolution obtained after reducing the second rendering resolution can accurately match the actual display content requirements of the target image frame. The first rendering resolution will not be too small or too large, which is beneficial to improving the accuracy of the first rendering resolution.

[0108] Furthermore, in this embodiment, step S01 includes: determining a first mean value corresponding to each of the image regions, wherein the first mean value is the mean value of all grayscale values ​​corresponding to all pixels in the image region; determining the mean value of all the first mean values ​​as a second mean value, and determining the standard deviation of all the first mean values ​​as a second standard deviation; determining a second grayscale interval based on the second mean value and the second standard deviation; and determining the resolution adjustment value based on the second mean value and the second grayscale interval.

[0109] The first mean here refers to the same concept as the first mean mentioned above. When step S20 includes step S21, step S01 here can be executed using the results above.

[0110] The second grayscale interval represents the range of the average grayscale value of the image region when the target image frame is uniform.

[0111] In this embodiment, an adjustment value is determined based on the second standard deviation. The second mean is then adjusted based on the adjustment value to obtain the interval thresholds (maximum and / or minimum thresholds) of the second grayscale interval. The range of grayscale values ​​defined by these interval thresholds is then used as the second grayscale interval. Specifically, the maximum and minimum thresholds of the second grayscale interval are obtained after adjusting the second mean based on the adjustment value. The set of all grayscale values ​​between the maximum and minimum thresholds is then defined as the second grayscale interval.

[0112] Specifically, in this embodiment, a preset multiple of the second standard deviation (greater than 1, which can be an integer multiple or a non-integer multiple) is used as the adjustment value. In other embodiments, the second standard deviation can also be used directly as the adjustment value.

[0113] In this embodiment, the adjustment value is the adjustment range, the difference between the second mean and the adjustment range is used as the minimum critical value of the second grayscale range, and the sum of the second mean and the adjustment range is used as the maximum critical value of the second grayscale range.

[0114] For example, if the second mean is μ2 and the second standard deviation is σ2, then the second gray range is [μ2-3σ2, μ2+3σ2].

[0115] Specifically, it is determined whether all the second mean values ​​corresponding to the image region or the second mean value of the target image region are located within the corresponding second grayscale range, and multiple judgment results are obtained. The resolution adjustment value is determined based on the multiple judgment results.

[0116] In addition, the magnitude or quantity relationship (e.g., difference) between all the second mean values ​​corresponding to the image region or the second mean value of the target image region and the critical value of the first gray level interval can be determined to obtain multiple recognition results, and the resolution adjustment value can be determined based on the multiple recognition results.

[0117] In this embodiment, by analyzing the mean and standard deviation of grayscale values ​​of multiple image regions, a second grayscale interval determined based on the mean and standard deviation is used to characterize the grayscale range when the target image frame is uniform overall. Thus, the second mean and the first grayscale interval of the image region can accurately determine the uniformity of the target image frame as a whole, which helps to improve the accuracy of the determined resolution adjustment value and the first rendering resolution determined based on the resolution adjustment value. This further improves the accuracy of the subsequently determined rendering resolution, further ensuring the display effect while reducing energy consumption.

[0118] Furthermore, in this embodiment, a third statistical quantity of the second means that is located within the second grayscale range is determined among all the second means; a third proportion of the third statistical quantity in the total number of the second means is determined; and a resolution adjustment value is determined based on the third proportion, wherein the resolution adjustment value is positively correlated with the third proportion.

[0119] In this embodiment, a resolution adjustment value is obtained by adjusting a preset adjustment value according to a third proportion. In this embodiment, the preset adjustment value is a second rendering resolution of 50%. Specifically, the product of the third proportion and the preset adjustment value can be used as the resolution adjustment value, and the product of the second rendering resolution and the resolution adjustment value is used as the first rendering resolution.

[0120] In this embodiment, the resolution adjustment value is determined by a certain method, which is beneficial for rendering with a smaller rendering resolution when the video content is uniform. As the complexity of the displayed content increases, the rendering resolution can be gradually reduced, thereby achieving an effective balance between display effect and energy saving.

[0121] Furthermore, based on any of the above embodiments, before the step of determining the uniformity analysis result of the corresponding image region based on the grayscale value of the pixel in the image region, the method further includes: calculating the grayscale value of the pixel by weighting the color value corresponding to the pixel according to the weight value corresponding to each of the preset color channels based on the color value of the pixel in multiple preset color channels.

[0122] Specifically, if the target image frame is an RGB image, then the multiple preset color channels are red, blue, and green channels. Each preset color channel corresponds to a different weight value, which is a parameter adjusted based on the human brightness perception system. The result of a weighted average of the color values ​​of each preset color channel according to the weight values ​​is used as the grayscale value corresponding to the pixel. Specifically, the grayscale value range is [0, 255].

[0123] In this embodiment, the above method helps to achieve both display quality and energy saving during the rendering process of color image display.

[0124] Furthermore, embodiments of the present invention also propose a storage medium storing an image rendering program, wherein the image rendering program, when executed by a processor, implements the relevant steps of any of the above embodiments of the image rendering method.

[0125] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0126] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0127] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, display device, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0128] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. An image rendering method, characterized in that, The image rendering method includes the following steps: Acquire the target image frame and divide the target image frame into multiple image regions; The uniformity analysis result of the corresponding image region is determined based on the gray value of the pixels in the image region. The uniformity analysis result includes whether the sub-images in the image region are uniform. The rendering resolution is determined based on the multiple uniformity analysis results corresponding to the multiple image regions; Render the target image frame according to the rendering resolution; The step of determining the rendering resolution based on the multiple uniformity analysis results corresponding to the multiple image regions includes: A second statistical quantity of target image regions is determined among the plurality of image regions, and the uniformity analysis result of the target image regions is the uniformity of the corresponding sub-images; Determine the second percentage of the second statistical quantity in the total number of the plurality of image regions; When the second proportion is greater than or equal to the second preset proportion, the first rendering resolution is determined to be the rendering resolution; When the second proportion is less than the second preset proportion, the second rendering resolution is determined to be the rendering resolution; Wherein, the first rendering resolution is less than the second rendering resolution, and before the step of determining the first rendering resolution as the rendering resolution when the second proportion is greater than or equal to the second preset proportion, the method further includes: determining a resolution adjustment value based on the grayscale values ​​of pixels in the plurality of image regions; reducing the second rendering resolution based on the resolution adjustment value to obtain the first rendering resolution.

2. The image rendering method as described in claim 1, characterized in that, The step of determining the uniformity analysis result of the corresponding image region based on the grayscale value of the pixels in the image region includes: Determine the first mean and first standard deviation of all gray values ​​corresponding to all pixels in the image region; The first grayscale range is determined based on the first mean and the first standard deviation; Whether the corresponding sub-image is uniform is determined based on the grayscale value of the pixels in the image region and the first grayscale range.

3. The image rendering method as described in claim 2, characterized in that, The step of determining whether the corresponding sub-image is uniform based on the gray values ​​of pixels in the image region and the first gray range includes: Determine a first statistical number of target pixels in the image region, wherein the gray value corresponding to the target pixel is located within the first gray range; Whether the corresponding sub-image is uniform is determined based on the first statistical count.

4. The image rendering method as described in claim 3, characterized in that, The step of determining whether the corresponding sub-image is uniform based on the first statistical quantity includes: Determine the first percentage of the first statistical quantity in the total number of pixels in the corresponding image region; When the first proportion is greater than or equal to the first preset proportion, the corresponding sub-image is determined to be uniform; When the first proportion is less than the first preset proportion, it is determined that the corresponding sub-image is uneven.

5. The image rendering method as described in claim 1, characterized in that, The step of determining the resolution adjustment value based on the grayscale values ​​of pixels in the plurality of image regions includes: A first mean value is determined for each of the image regions, wherein the first mean value is the mean value of all gray values ​​corresponding to all pixels in the image region; The mean of all the first means is determined to be the second mean, and the standard deviation of all the first means is determined to be the second standard deviation; The second grayscale range is determined based on the second mean and the second standard deviation; The resolution adjustment value is determined based on the second mean and the second grayscale range.

6. The image rendering method as described in claim 5, characterized in that, The step of determining the resolution adjustment value based on the second mean and the second grayscale range includes: Determine the third statistical number of the second means that are located within the second grayscale interval among all the second means; Determine the third percentage of the total number of the third statistical quantity relative to the second mean; The resolution adjustment value is determined based on the third proportion, and the resolution adjustment value is positively correlated with the third proportion.

7. The image rendering method according to any one of claims 1 to 6, characterized in that, Before the step of determining the uniformity analysis result of the corresponding image region based on the grayscale values ​​of pixels in the image region, the method further includes: Based on the color values ​​corresponding to the pixel in multiple preset color channels; The grayscale value of the pixel is obtained by weighting the color value of the pixel according to the weight value corresponding to each preset color channel.

8. A display device, characterized in that, The display device includes: a memory, a processor, and an image rendering program stored in the memory and executable on the processor, wherein the image rendering program, when executed by the processor, implements the steps of the image rendering method as described in any one of claims 1 to 7.

9. A storage medium, characterized in that, The storage medium stores an image rendering program, which, when executed by a processor, implements the steps of the image rendering method as described in any one of claims 1 to 7.

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