WO2019041112A1

WO2019041112A1 - Image processing method and apparatus

Info

Publication number: WO2019041112A1
Application number: PCT/CN2017/099365
Authority: WO
Inventors: 李蒙; 陈海; 郑建铧; 余全合
Original assignee: 华为技术有限公司
Priority date: 2017-08-28
Filing date: 2017-08-28
Publication date: 2019-03-07

Abstract

Embodiments of the present application relates to the technical field of image processing, and provides an image processing method and apparatus, capable of resolving the problems of image delay and flickering. The method comprises: obtaining a reference value of a target parameter of a previous adjacent frame of an image frame to be processed, the target parameter being used for representing a displayed content performance indicator of an image frame; according to a pixel value of an obtained image frame, calculating a statistical value of the target parameter of the image frame to be processed; calculating an absolute value of the difference between the reference value and the statistical value; according to the absolute value, calculating an update coefficient using a hyperbolic tangent function; according to the update coefficient, the reference value, and the statistical value, calculating an updated statistical value of the target parameter of the image frame to be processed using a time-domain filter function; according to the updated statistical value, calculating a display adaptation parameter of the image frame to be processed, the display adaptation parameter being used for adjusting the dynamic range and color of the image frame to be processed; and according to the display adaptation parameter, adjusting the image frame to be processed.

Description

Image processing method and device

Technical field

The embodiments of the present invention relate to the field of image processing technologies, and in particular, to an image processing method and apparatus.

Background technique

A High Dynamic Range (HDR) image is a type of image that represents a large dynamic range of brightness changes from direct sunlight to the darkest shadow, which can represent a range of brightness from 10 ^-3 to 10 ⁶ candelas. / square meter (cd/m ² ). At present, the dynamic range of the image that can be displayed by the display device is limited, that is, the dynamic range represented by one HDR image cannot be displayed. Therefore, it is generally necessary to compress the dynamic range of the HDR image to adjust the high dynamic range of the HDR image to display within the display capability of the display device.

Adjusting the dynamic range of the HDR image generally needs to be performed according to the target parameters carried in the video stream. For a video code stream carrying a plurality of HDR image frames, the target parameter carried by the video code stream is obtained by the image processing device by calculating pixels of all image frames in the code stream, and the target parameter is used to represent the code stream. Display content performance indicators of all image frames (generally, the target parameters carried by the code stream may also be referred to as metadata carried by the code stream). However, the scenes of different image frames in the code stream may be different. Therefore, it is difficult to ensure the effect of adjusting the dynamic range of each image frame using the target parameters carried by the code stream. In addition, in some application scenarios, such as a live application scenario, a non-standard code stream, etc., the code stream obtained by the image processing device may be missing all or part of the target parameters. Therefore, the existing image processing device uses the target parameter adjustment of the image frame. The dynamic range of the image frame. The target parameter of the image frame is used to characterize the display content performance indicator of the image frame.

Specifically, the image processing device acquires a statistical value of the target parameter of the current image frame, and uses the reference value of the target parameter of the previous image frame and a fixed update coefficient (generally 0.1) to calculate the update of the target parameter of the current image frame. The statistical value, and then adjust the dynamic range of the current image frame according to the calculated updated statistical value. Due to the need for real-time playback, the statistical value of the target parameter of the current image frame is generally approximated using the target parameter of the previous adjacent frame of the current frame. The value of the existing update coefficient is a fixed value. If the fixed value is selected to be small, the update value of the target value of the HDR image is slower. Thus, when the image scene is switched, the statistical value of the target parameter of the HDR image frame is HDR image frames cannot be synchronized, resulting in large delays in HDR image frames. If the fixed value is selected to be large, the statistical value of the target parameter of the HDR image is updated faster, so that when the image scene is switched, the statistical value of the target parameter of the HDR image frame cannot be synchronized with the HDR image frame, causing the HDR image frame to flicker. .

Summary of the invention

The present application provides an image processing method and apparatus, which effectively solve the problems of delay, flicker, and the like of an HDR image frame.

To achieve the above objectives, the present application adopts the following technical solutions:

In a first aspect, an image processing method is provided. The image processing device acquires a reference value of a target parameter of a previous adjacent frame of an image frame to be processed, and calculates a to-be-processed image frame according to the pixel value of the acquired image frame. Head After the statistical value of the parameter is calculated, the absolute value of the difference between the reference value and the statistical value is calculated. Here, the target parameter is used to represent the display content performance index of the image frame; the image processing device uses the double according to the calculated absolute value. a curve tangent function, calculating an update coefficient, and further calculating an updated statistical value of a target parameter of the image frame to be processed by using a time domain filter function according to the update coefficient, the reference value, and the statistical value, so that the image processing device can Based on the calculated updated statistical value, a display adaptation parameter for adjusting a dynamic range and a color of the image frame to be processed is calculated, so that the image processing apparatus adjusts the image frame to be processed according to the display adaptation parameter.

Image scene switching refers to a significant change in the content of an image. Generally, when the image scene is switched, the difference between the statistical values of the target parameters of the adjacent two image frames is large. The image processing apparatus in the embodiment of the present application calculates an absolute value of a difference between a reference value of a target parameter of a previous adjacent frame of a to-be-processed image frame and a statistical value of a target parameter of the image frame to be processed, and according to the absolute Value, using the hyperbolic tangent function to calculate the update coefficient. Since the hyperbolic tangent function has a monotonous increment, and the change characteristic of the curve is that the two ends are more intense and the middle is more gradual, the image processing apparatus can also obtain a larger update coefficient when the absolute value is large. In this way, the image processing apparatus can quickly update the statistical value of the target parameter of the image frame to be processed, and quickly realize the synchronization between the statistical value of the target parameter of the image frame to be processed and the adjusted image frame to be processed, thereby effectively solving the image delay. The problem, and it will not cause the image to flicker because the update factor is too large.

Optionally, in a possible implementation manner of the present application, the “image processing apparatus calculates a update coefficient by using a hyperbolic tangent function according to the calculated absolute value” is: the image processing apparatus calculates according to the following formula: Update factor:

Where A is the above update coefficient, x is the above absolute value, a is the first preset value, and b is the second preset value.

The image processing apparatus can accurately recognize whether or not the image scene is switched according to the hyperbolic tangent function. Optionally, in the above formula for calculating the update coefficient, a=3, b=0.5.

Optionally, in another possible implementation manner of the present application, the image processing apparatus obtains a code stream corresponding to the multiple image frames before acquiring the reference value of the target parameter of the previous adjacent frame of the image frame to be processed. The image frame to be processed is the t-th image frame of the plurality of image frames corresponding to the code stream, and t is a non-negative integer. In this case, the above-described method of "the image processing apparatus calculates the updated statistical value of the target parameter of the image frame to be processed by using the time domain filter function according to the update coefficient, the reference value, and the statistical value" is: the image processing apparatus adopts The above-mentioned updated statistical value M _t is calculated by the following formula: when t>0, M _t =A×C _t +B×M _t-1 ; when t=0, M _t =C ₀ ; wherein A is The update coefficient, C _t is the above-mentioned statistical value, B is the third preset value, M _t-1 is the above reference value, C ₀ is the fourth preset value, or C ₀ is obtained by parsing the above code stream.

Optionally, in another possible implementation manner of the present application, in the foregoing formula for calculating the updated statistical value M _t of the target parameter of the image frame to be processed, B=1-A.

For the first image frame of the plurality of image frames, the image processing apparatus may determine a parameter preset in the system as a statistical value of the target parameter of the image frame, or obtain a statistical value of the target parameter of the image frame by parsing the code stream. . For any image frame other than the first image frame of the plurality of image frames, the image processing device needs to utilize the statistical value of the target parameter of the image frame, and the target parameter of the previous adjacent image frame of the image frame. The reference value and the update coefficient are used to determine an updated statistical value of the target parameter of the image frame, and the update determined by the method is The subsequent statistics are more accurate.

It is easy to understand that the parameter value of the target parameter of the previous adjacent image frame of the image frame to be processed is substantially: the image processing device calculates the dynamic range and color of the previous image frame of the image frame to be processed before adjusting the dynamic range and color of the previous image frame of the image frame to be processed. The updated statistical value of the target parameter of the previous adjacent image frame of the image frame to be processed. For ease of understanding, the present application is expressed by reference values.

Optionally, in another possible implementation manner of the present application, in the case that the to-be-processed image frame is the t-th image frame of the plurality of image frames, the foregoing “image processing apparatus is configured according to the acquired image frame. a pixel value, a method for calculating a statistical value of a target parameter of an image frame to be processed": the image processing device calculates a target parameter of the tith image frame according to a pixel value of the tith image frame in the plurality of image frames, and The target parameter of the tith image frame is a statistical value of the target parameter of the image frame to be processed, and i is a positive integer.

In the case that the image processing apparatus processes the code stream in real time, if the image frame to be processed includes more pixels, the image processing apparatus calculates the statistical value of the target parameter of the image frame to be processed, which takes a long time, and is easy to appear. Delayed issue. If the image frame to be processed includes few pixels, the image processing device can calculate the statistical value of the target parameter of the image frame to be processed in time. In order to avoid the delay problem, for the t-th image frame, the image processing apparatus uses the target parameter of the t-ith image frame as the statistical value of the target parameter of the t-th image frame.

Optionally, in another possible implementation manner of the present application, the target parameter includes a maximum brightness value of the display content, a maximum image average brightness value of the display content, a maximum value of the nonlinear brightness component of the display content, and a nonlinear brightness component of the display content. Minimum value, display content nonlinear brightness component average value, display content nonlinear brightness component standard variance value, display content nonlinear brightness scaling quantization, display content nonlinear brightness gamma value and display content nonlinear chromaticity scaling At least one of the quantifications.

In particular, the non-linear luminance component of the display content is a non-linear Y component of the display content, and the non-linear chrominance component of the display content is a non-linear Cb/Cr component of the display content.

In a second aspect, an image processing apparatus is provided, the image processing apparatus including an acquisition unit, a calculation unit, and an adjustment unit. Specifically, the acquiring unit is configured to acquire a plurality of image frames, and obtain reference values of target parameters of a previous adjacent frame of the image frames to be processed in the plurality of image frames, where the target parameters are used to represent display content performance of the image frames. index. The calculating unit is configured to calculate a statistic value of the target parameter of the image frame to be processed according to the pixel value of the acquired image frame acquired by the acquiring unit, and calculate a difference between the reference value and the statistic value acquired by the acquiring unit. An absolute value of the value, and a method for calculating an update coefficient by using a hyperbolic tangent function according to the absolute value, and for calculating a target parameter of the image frame to be processed by using a time domain filter function according to the update coefficient, the reference value, and the statistical value The updated statistical value is used to calculate display adaptation parameters of the image frame to be processed according to the updated statistical value, and the display adaptation parameter is used to adjust the dynamic range and color of the image frame to be processed. The adjusting unit is configured to adjust an image frame to be processed according to the display adaptation parameter calculated by the calculating unit.

Further, in a possible implementation manner of the application, the calculating unit is specifically configured to:

Calculate the update factor according to the following formula:

Further, in another possible implementation manner of the present application, the acquiring unit is further configured to obtain a code stream corresponding to multiple image frames, where the image frame to be processed is in a plurality of image frames corresponding to the code stream. The tth image frame, t is a non-negative integer. The calculation unit is specifically configured to: calculate the updated statistical value M _t by using the following formula: when t>0, M _t =A×C _t +B×M _t-1 ; when t=0, M _t =C ₀ ; where A is the above update coefficient, C _t is the above statistical value, B is the third preset value, M _t-1 is the above reference value, C ₀ is the fourth preset value, or C ₀ is Obtained by parsing the above code stream.

Further, in another possible implementation manner of the present application, in the formula for calculating the updated statistical value M _t of the image frame to be processed, B=1-A.

Further, in another possible implementation manner of the present application, in a case that the to-be-processed image frame is the t-th image frame of the plurality of image frames, the calculating unit is further configured to use the multiple images according to the foregoing The pixel value of the tith image frame in the frame, and the target parameter of the tith image frame is calculated, and i is a positive integer. Correspondingly, the image processing apparatus in the present application further includes a determining unit, configured to use the target parameter of the t-ith image frame calculated by the calculating unit as a statistical value of a target parameter of the image frame to be processed.

Further, in another possible implementation manner of the present application, the target parameter includes a maximum brightness value of the display content, a maximum image average brightness value of the display content, a maximum value of the nonlinear brightness component of the display content, and a minimum value of the nonlinear brightness component of the display content. At least one of a display content nonlinear luminance component average value, a display content nonlinear luminance component standard variance value, a display content nonlinear luminance scaling quantization, a display content nonlinear luminance gamma value, and a display content nonlinear chrominance scaling quantization .

For a detailed description of the second aspect and various implementations of the present application, reference may be made to the detailed description of the first aspect and various implementations thereof; and the beneficial effects of the second aspect and various implementations thereof may be referred to The analysis of the beneficial effects on the one hand and its various implementations will not be repeated here.

In a third aspect, an image processing method is provided, the image processing device acquires display parameters of a display device, and the image processing device acquires, from the code stream, target parameters for characterizing display content performance indicators of all image frames in the code stream; The processing device calculates an adjustment coefficient according to the display parameter and the target parameter, and updates the acquired target parameter according to the adjustment coefficient; the image processing device sends the updated target parameter to the display device, so that the display device adjusts according to the updated target parameter. The dynamic range and color of the image frame.

The image processing device calculates an adjustment coefficient according to the display parameter of the current display device and the target parameter acquired from the code stream, and then updates the target parameter according to the adjustment coefficient, so that the updated target parameter is adapted to the display parameter of the display device, which is convenient. The display device directly adjusts each image frame with the updated target parameters.

Optionally, in a possible implementation manner of the present application, the foregoing display parameter includes a maximum display brightness value of the display device, where the target parameter includes a maximum brightness value of the display content, and the adjustment coefficient includes a linear domain adjustment coefficient and a nonlinear domain adjustment. Coefficient, correspondingly, the above method "the image processing device calculates the adjustment parameter according to the display parameter" is: the image processing device calculates the linear domain adjustment coefficient and the nonlinearity respectively according to the maximum brightness value of the display content and the maximum display brightness value of the image processing device The domain adjustment coefficient, specifically, the image processing device calculates the linear domain adjustment coefficient by the following formula:

Linear_adjust_factor

=min(1.0,Max_Display_Target_Luminance/Max_Content_Light_Level)

The linear_adjust_factor is the linear domain adjustment coefficient, the Max_Display_Target_Luminance is the maximum display brightness value of the display device, and the Max_Content_Light_Level is the maximum brightness value of the display content. Min(1.0, Max_Display_Target_Luminance/Max_Content_Light_Level) indicates the minimum value of 1.0 and Max_Display_Target_Luminance/Max_Content_Light_Level.

The image processing apparatus calculates the nonlinear domain adjustment coefficient using the following formula:

Wherein, the nonlinear_adjust_factor is the above-mentioned nonlinear domain adjustment coefficient, and the OETF (·) represents the photoelectric conversion function.

Optionally, in another possible implementation manner of the present application, the target parameter further includes: a maximum image average brightness value of the display content, a maximum value of the nonlinear brightness component of the display content, a minimum value of the nonlinear brightness component of the display content, and a display content. At least one of a nonlinear luminance component average value, a display content nonlinear luminance component standard variance value, a display content nonlinear luminance scaling quantization, a display content nonlinear luminance gamma value, and a display content nonlinear chrominance scaling quantization. Correspondingly, the method for updating the target parameter according to the adjustment coefficient by the image processing apparatus is specifically: the image processing apparatus multiplies the linear domain adjustment coefficient by the maximum brightness value of the display content, and quantizes it into an unsigned integer to obtain an updated display. The maximum brightness value of the content; when the target parameter includes the maximum image average brightness value of the display content, the image processing device multiplies the linear domain adjustment coefficient by the maximum image average brightness value of the display content, and quantizes it into an unsigned integer to obtain an updated display. Content maximum image average brightness value; when the target parameter includes a maximum value of the display content nonlinear brightness component, the image processing device multiplies the nonlinear domain adjustment coefficient by the display content nonlinear brightness component maximum value, and quantizes to an unsigned integer, Obtaining a maximum value of the non-linear luminance component of the updated display content; when the target parameter includes a minimum value of the nonlinear luminance component of the display content, the image processing device multiplies the nonlinear domain adjustment coefficient by the minimum value of the nonlinear luminance component of the display content, and Quantify as an unsigned integer and get updated The display content non-linear luminance component minimum value; when the target parameter includes the average value of the display content nonlinear luminance component, the image processing device multiplies the nonlinear domain adjustment coefficient by the display content nonlinear luminance component average value, and quantizes to none a symbol integer, which obtains an average value of the updated non-linear luminance component of the display content; when the target parameter includes a standard variance value of the non-linear luminance component of the display content, the image processing apparatus sets the nonlinear domain adjustment coefficient and the display content nonlinear luminance component standard The variance values are multiplied and quantized into unsigned integers to obtain an updated standard deviation of the nonlinear luminance components of the display content; when the target parameters include non-linear luminance scaling quantization of the display content, the image processing apparatus displays the content nonlinearity The value of the brightness scaling quantization is set to a first preset threshold; when the target parameter includes the display content nonlinear chrominance scaling quantization, the image processing device sets the value of the display content nonlinear chrominance scaling quantization to a second preset threshold; When the above target parameters include non-linear brightness of display content When the value of the horse, the non-linear luminance setting value display gamma value content third predetermined threshold value.

In a fourth aspect, an image processing apparatus is provided, the image processing apparatus comprising an acquisition unit, a calculation unit, an update unit, and a transmission unit. Specifically, the acquiring unit is configured to acquire display parameters of the display device, and to obtain a target parameter from the code stream, where the target parameter is used to represent a display content performance indicator of all image frames in the code stream. The calculating unit is configured to calculate an adjustment coefficient according to the display parameter and the target parameter acquired by the acquiring unit. The updating unit is configured to update the target parameter acquired by the acquiring unit according to the adjustment coefficient calculated by the calculating unit. The sending unit is configured to send, to the display device, the updated target parameter obtained by the updating unit, so that the display device adjusts the dynamic range and color of the image frame according to the updated target parameter.

Further, in a possible implementation manner of the present application, the foregoing display parameter includes a display device The display unit displays a brightness value, and the target parameter displays a maximum brightness value of the content. The adjustment coefficient includes a linear domain adjustment coefficient and a nonlinear domain adjustment coefficient. The calculation unit is specifically configured to: display a maximum brightness value according to the content and a maximum display brightness value of the image processing device. Calculate the linear domain adjustment factor using the following formula:

Linear_adjust_factor

=min(1.0,Max_Display_Target_Luminance/Max_Content_Light_Level)

Wherein, linear_adjust_factor is a linear domain adjustment coefficient, Max_Display_Target_Luminance is a maximum display brightness value of the display device, Max_Content_Light_Level is a maximum brightness value of the display content, and min(1.0, Max_Display_Target_Luminance/Max_Content_Light_Level) represents a minimum value of 1.0 and Max_Display_Target_Luminance/Max_Content_Light_Level;

According to the maximum brightness value of the display content and the maximum display brightness value of the display device, the nonlinear domain adjustment coefficient is calculated by the following formula:

Wherein, the nonlinear_adjust_factor is the nonlinear domain adjustment coefficient, and the OETF (·) represents the photoelectric conversion function.

Further, in another possible implementation manner of the present application, the target parameter further includes: a maximum image average brightness value of the display content, a maximum value of the nonlinear brightness component of the display content, a minimum value of the nonlinear brightness component of the display content, and a non-display content. At least one of a linear luminance component average value, a display content nonlinear luminance component standard variance value, a display content nonlinear luminance scaling quantization, a display content nonlinear luminance gamma value, and a display content nonlinear chrominance scaling quantization. Correspondingly, the updating unit is specifically configured to: multiply the linear domain adjustment coefficient by the maximum brightness value of the display content, and quantize to an unsigned integer to obtain an updated maximum brightness value of the display content; and when the target parameter includes the maximum image of the display content. When the average brightness value is obtained, the linear domain adjustment coefficient is multiplied by the maximum image average brightness value of the display content, and quantized into an unsigned integer to obtain an updated image maximum brightness value of the display content; when the target parameter includes the above-mentioned display content nonlinear brightness When the component maximum value is multiplied, the nonlinear domain adjustment coefficient is multiplied by the maximum value of the nonlinear luminance component of the display content, and quantized into an unsigned integer, and the updated maximum nonlinear luminance component of the display content is obtained; when the target parameter includes the above display content When the nonlinear luminance component is the minimum value, the nonlinear domain adjustment coefficient is multiplied by the minimum value of the nonlinear luminance component of the display content, and quantized into an unsigned integer, and the minimum value of the nonlinear luminance component of the updated display content is obtained; when the target parameter includes When the above average content of the nonlinear luminance component is displayed, The linear domain adjustment coefficient is multiplied by the average value of the nonlinear luminance component of the display content, and quantized into an unsigned integer to obtain an average value of the updated nonlinear luminance component of the display content; when the target parameter includes the standard deviation of the nonlinear luminance component of the display content described above; In the value, the nonlinear domain adjustment coefficient is multiplied by the standard variance value of the non-linear luminance component of the display content, and quantized into an unsigned integer, and the updated standard deviation of the nonlinear brightness component of the display content is obtained; when the target parameter includes the above When displaying the content nonlinear brightness scaling quantization, the value of the content non-linear brightness scaling quantization is set to a first preset threshold; when the target parameter includes the display content nonlinear chromaticity scaling quantization, the content nonlinear chromaticity scaling quantization is displayed. The value is set to a second preset threshold; when the target parameter includes the display content non-linear luminance gamma value, the value of the display content nonlinear luminance gamma value is set to a third preset threshold.

For a detailed description of the fourth aspect of the present application and various implementations thereof, reference may be made to the detailed description in the third aspect and various implementation manners thereof; and the beneficial effects of the fourth aspect and various implementation manners thereof may be referred to three The analysis of the beneficial effects in aspects and various implementations thereof will not be repeated here.

In a fifth aspect, an image processing apparatus is provided, the image processing apparatus comprising: one or more processors, a memory, and a communication interface. Wherein the memory, communication interface is coupled to one or more processors; the image processing device is in communication with other devices via a communication interface; the memory is for storing computer program code, the computer program code comprising instructions, when the one or more processors perform the When instructed, the image processing apparatus performs the image processing method as described in the foregoing first aspect and any one of its possible implementations or the image processing method as described in the foregoing third aspect and any one of its possible implementations.

In a sixth aspect, a computer storage medium is provided having stored therein computer program code. When the processor of the image processing apparatus in the fifth aspect executes the computer program code, the image processing apparatus performs the image processing method as described in the foregoing first aspect and any one of its possible implementation manners or performs the third aspect as described above And an image processing method as described in any of the possible implementations.

A seventh aspect, further provides a computer program product comprising instructions, when executed on an image processing device, causing the image processing device to perform an image processing method as described in the first aspect above and any one of its possible implementations Or an image processing method as described in the foregoing third aspect and any one of the possible implementations.

In the present application, the name of the above image processing apparatus is not limited to the device or the function module itself. In actual implementation, these devices or function modules may appear under other names. As long as the functions of the respective devices or functional modules are similar to the present application, they are within the scope of the claims and their equivalents.

For a detailed description of the fifth aspect, the sixth aspect, the seventh aspect, and various implementations thereof, reference may be made to the detailed description in the first aspect and various implementations thereof, or to the third aspect and various implementations thereof. A detailed description of the manner; and the beneficial effects of the second aspect, the third aspect, the fourth aspect, the fifth aspect, and various implementations thereof, may refer to the beneficial effects analysis in the first aspect and various implementation manners thereof, Or refer to the beneficial effects analysis in the third aspect and various implementation manners thereof, and details are not described herein again.

These and other aspects of the embodiments of the present application will be more apparent from the following description.

DRAWINGS

FIG. 1 is a schematic structural diagram of an image processing system according to an embodiment of the present application;

2 is a schematic structural diagram of hardware of an electronic device according to an embodiment of the present application;

FIG. 3 is a schematic flowchart 1 of an image processing method according to an embodiment of the present disclosure;

4 is a graph of a hyperbolic tangent function provided by an embodiment of the present application;

FIG. 5 is a second schematic flowchart of an image processing method according to an embodiment of the present disclosure;

FIG. 6 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present application.

Detailed ways

The terms "first", "second", and "third" and the like in the specification and claims of the present application and the above drawings are used to distinguish different objects, and are not intended to limit the specific order.

In the embodiments of the present application, the words "exemplary" or "such as" are used to mean an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of the words "exemplary" or "such as" is intended to present the concepts in a particular manner.

In many fields, the dynamic range is represented by the ratio between the maximum and minimum values of a variable. In general, the dynamic range of an image can be represented by the ratio between the maximum brightness value and the minimum brightness value of the displayed image.

An HDR image is an image with a very wide range of brightness, which is different from the storage format of a normal image. Joint Photographic Experts Group (JPEG), image file format (Bitmap, BMP) images use 8-bit integer data to store individual channel components, for example: for red (R, R) channel components, green (Green) , G) and blue (Blue, B), each channel component of the ordinary image is saved with 8-bit shaping data, and a single pixel has a total of 24 bits. Each channel component of the HDR image is represented by a floating point number, and each channel component is stored in 32-bit data, so that the dynamic range of the image is preserved to the utmost extent.

The luminance of the HDR image ranges from 10 ^-3 to 10 ⁶ cd/m ² , so the HDR image can realistically represent the real world. The HDR image is capable of recording brightness over the entire visible range and is capable of supporting dynamic range and color gamut equivalent to the color gamut of human visual features.

Generally, a display device having a display dynamic range of less than 0.1 to 400 cd/m ² is referred to as an LDR display device, and a display device having a display dynamic range of more than 0.01 to 540 cd/m ² is referred to as an HDR display device. The display dynamic range of different HDR display devices is different, for example, an HDR display device of 0.01 to 540 cd/m ^{2 ,} an HDR display device of 0.005 to 1000 cd/m ² , and the like.

Since the dynamic range of the image that the LDR display device can display is limited, the display dynamic range of different HDR display devices is different. Therefore, when the HDR image is displayed by the LDR display device and the HDR display device, adaptive adjustment (compression or stretching is required). The dynamic range of the HDR image is sufficient to display the HDR image clearly and perfectly.

Currently, image processing devices use the target parameters of an image frame to adjust the dynamic range of an image frame. The target parameter of the image frame is used to characterize the display content performance indicator of the image frame. Specifically, the image processing device acquires a statistical value of the target parameter of the current image frame, and uses the reference value of the target parameter of the previous image frame and a fixed update coefficient (generally 0.1) to calculate the update of the target parameter of the current image frame. The statistical value, and then adjust the dynamic range of the current image frame according to the calculated updated statistical value. Due to the need for real-time playback, the statistical value of the target parameter of the current image frame is generally approximated using the target parameter of the previous adjacent frame of the current frame. The value of the existing update coefficient is a fixed value. If the fixed value is selected to be small, the update value of the target value of the HDR image is slower. Thus, when the image scene is switched, the statistical value of the target parameter of the HDR image frame is HDR image frames cannot be synchronized, resulting in a large delay in the HDR image. If the fixed value is selected to be large, the statistical value of the target parameter of the HDR image is updated faster, so that when the image scene is switched, the statistical value of the target parameter of the HDR image frame cannot be synchronized with the HDR image frame, resulting in flickering of the HDR image.

The image processing device provides an image processing method and device, and the image processing device obtains a reference value of a target parameter of a previous adjacent frame of the image frame to be processed and a statistical value of a target parameter of the image frame to be processed, And calculating an absolute value of the difference between the two, and then the image processing device calculates the update coefficient by using the hyperbolic tangent function, and further calculates the update coefficient, the reference value, and The statistical value is used to calculate the updated statistical value of the target parameter of the image frame to be processed by using the time domain filter function. Finally, the image processing apparatus calculates the image frame to be processed according to the calculated updated statistical value. The dynamic range and color display adaptation parameters cause the image processing device to adjust the image frame to be processed according to the display adaptation parameters. Since the hyperbolic tangent function has a monotonous increment, and the change characteristic of the curve is that the two ends are relatively sharp and the middle is gentle, the image processing apparatus can also obtain an appropriate update coefficient when the absolute value is large. In this way, the image processing apparatus can quickly update the statistical value of the target parameter of the image frame to be processed, and quickly realize the statistical value of the target parameter of the image frame to be processed and the adjusted image frame to be processed. Synchronization effectively solves the problem of image delay; and it does not cause the image frame to flicker due to the excessive selection of the update coefficient, effectively avoiding the problem of image flicker.

The image processing method provided by the embodiment of the present application is applicable to an image processing system. FIG. 1 is a schematic structural diagram of an image processing system according to an embodiment of the present application. As shown in FIG. 1, the image processing system includes an image processing device 10 and a display device 11, and the image processing device 10 communicates with the display device 11.

In practical applications, the connection between the image processing apparatus 10 and the display device 11 may be a wired connection or a wireless connection, and the connection relationship between the image processing apparatus 10 and the display apparatus 11 is conveniently and intuitively represented in FIG. It is indicated by a solid line.

Specifically, the image processing device 10 can acquire the dynamic range supported by the display device 11, and after acquiring the code streams corresponding to the plurality of image frames, the image processing device 10 adjusts the dynamic range of each image frame to adjust The dynamic range of each subsequent image frame is matched with the dynamic range supported by the display device 11, and the image processing device 10 transmits each of the adjusted image frames to the display device 11 after acquiring the adjusted image frames. It is convenient for the display device 11 to display the adjusted image frame clearly and completely.

Optionally, the image processing apparatus 10 may acquire a code stream corresponding to multiple image frames from a network accessed by the image processing apparatus, or may receive corresponding multiples sent by other electronic devices that establish a communication connection with the image processing apparatus. The code stream of the image frame is not specifically limited in this embodiment of the present application.

The image processing device 10 and the display device 11 in the embodiments of the present application may each be an electronic device. Optionally, the image processing device 10 and the display device 11 in the embodiment of the present application may be independent of each other, or may be integrated in the same electronic device. In FIG. 1, the image processing apparatus 10 and the display device 11 are independently provided as an example.

For example, if the image processing apparatus 10 and the display device 11 in the embodiment of the present application are independent of each other, the image processing apparatus 10 in the embodiment of the present application may be a set top box, and the display apparatus 11 may be a television set.

If the image processing device 10 and the display device 11 are integrated in the same electronic device, the electronic device may be a mobile phone, a camera, a wearable device, an augmented reality (AR), a virtual reality (VR) device, or a tablet. Any device having an image display function, such as a computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, and a personal digital assistant (PDA), is not limited in this embodiment.

The image processing device 10 and the display device 11 in the embodiments of the present application may each be an electronic device. For the hardware structure of the electronic device in the embodiment of the present application, reference may be made to the constituent components of the electronic device shown in FIG. 2.

It should be understood that the illustrated electronic device is only one example of the image processing device 10 and the display device 11, and the electronic device may have more or fewer components than those shown in the figures, and two or more may be combined. Many components, or can have different component configurations. The various components shown in FIG. 2 may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and/or application specific integrated circuits.

As shown in FIG. 2, the electronic device may specifically include: a processor 21, a power source 22, a memory 23, an input unit 24, an audio circuit 25, and the like. It will be understood by those skilled in the art that the electronic device structure illustrated in FIG. 2 does not constitute a limitation to the electronic device, and may include more or less components than those illustrated, or a combination of certain components, or different component arrangements.

The specific components of the electronic device will be specifically described below with reference to FIG. 2:

The processor 21 is a control center of the electronic device, and connects various parts of the entire electronic device by using various interfaces and lines. In part, the electronic device is integrally monitored by running or executing software programs and/or modules stored in the memory 23, and recalling data stored in the memory 23, performing various functions and processing data of the electronic device. Alternatively, processor 21 may include one or more processing units. Optionally, the processor 21 can integrate an application processor and a modem processor. The application processor mainly processes an operating system, a user interface, an application, and the like; the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor and processor 21 can also be independent of each other.

The electronic device includes a power source 22 (such as a battery) for supplying power to each component. Alternatively, the power source 22 can be logically connected to the processor 21 through a power management system to manage functions such as charging, discharging, and power management through the power management system. .

The memory 23 can be used to store software programs and modules, and the processor 21 executes various functional applications and data processing of the electronic device by running software programs and modules stored in the memory 23. The memory 23 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application required for at least one function (such as receiving data function, image processing function, etc.), and the like; the storage data area may be stored according to Data created by the use of electronic devices (such as images, videos, etc.). Further, the memory 23 may include a high speed random access memory, and may also include a nonvolatile memory such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The input unit 24 can be configured to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the electronic device. Alternatively, the input unit 24 may include a touch screen 241 and other input devices 242. The touch screen 241, also referred to as a touch panel, can collect touch operations on or near the user (such as the operation of the user using any suitable object or accessory on the touch screen 241 or near the touch screen 241 using a finger, a stylus, etc.), and according to The preset program drives the corresponding connection device. Alternatively, the touch screen 241 may include two parts of a touch detection device and a touch controller. Wherein, the touch detection device detects the touch orientation of the user, and detects a signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts the touch information into contact coordinates, and sends the touch information. The processor 21 is provided and can receive commands from the processor 21 and execute them. In addition, the touch screen 241 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic waves.

The audio circuit 25 can include a speaker 251 and a microphone 252 for providing an audio interface between the user and the electronic device. The audio circuit 25 can transmit the converted electrical data of the received audio data to the speaker 251, and is converted by the speaker 251 into a sound signal output; on the other hand, the microphone 252 converts the collected sound signal into an electrical signal, and the audio circuit 25 After receiving, it is converted into audio data, and the audio data is output to the memory 23 for further processing.

Optionally, as shown in FIG. 2, the electronic device further includes a display unit 25 and a camera 26. Since the display unit 26 and the camera 27 are optional, they are indicated by dashed lines in FIG.

The display unit 26 can be used to display information input by the user or information provided to the user as well as various menus of the electronic device. The display unit 26 can include a display panel 261. Alternatively, the display panel 261 can be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like. Further, the touch screen 241 may cover the display panel 261, and when the touch screen 241 detects a touch operation on or near it, transmits to the processor 21 to determine the type of the touch event, and then the processor 21 displays the panel according to the type of the touch event. A corresponding visual output is provided on the 261. Although, in Figure 2 The touch screen 241 and the display panel 261 are implemented as two separate components to implement input and output functions of the electronic device, but in some embodiments, the touch screen 241 can be integrated with the display panel 261 to implement input and output of the electronic device. Features.

The camera 27 can also be used as an input device for converting the collected analog video or image signal into a digital signal and storing it in the memory 23. Specifically, the camera 27 may include a front camera, a rear camera, a built-in camera, an external camera, and the like, which are not limited in this embodiment.

Hereinafter, an image processing method provided by an embodiment of the present application will be described in detail in conjunction with specific embodiments. For convenience of description, the following description will be made by taking an image processing apparatus and a display device independently of each other as an example.

FIG. 3 is a schematic flowchart diagram of an image processing method according to an embodiment of the present disclosure, and the image processing method can be applied to the image processing system shown in FIG. 2 .

As shown in FIG. 3, the image processing method includes:

S300. The image processing device obtains a code stream corresponding to the plurality of image frames.

The image frames involved in the embodiments of the present application all refer to HDR image frames.

Optionally, the image processing device may acquire a code stream corresponding to the plurality of image frames from a network accessed by the image processing device, or may receive a corresponding plurality of images sent by other electronic devices that establish a communication connection with the image processing device. The code stream of the frame is not specifically limited in this embodiment of the present application.

Exemplarily, if the image processing device is a digital set top box, the digital set top box receives the high frequency signal from the wired network, and obtains a code stream corresponding to the plurality of image frames by demodulating the received high frequency signal.

As can be seen from the foregoing description, the image processing apparatus can acquire the dynamic range supported by the display device by communicating with the display device. In order to facilitate the display device to clearly and completely display the image frames acquired by the image processing device, the image processing device performs a process of adjusting the dynamic range of each image frame. Specifically, the image processing apparatus repeatedly performs the following S301-S306 to complete the adjustment of the dynamic range of the image frame.

The processing procedure of the image processing apparatus is the same for each image frame. The embodiment of the present application is only described by taking an example in which the image processing apparatus adjusts the dynamic range of the image frame to be processed. The image frame to be processed is any one of the plurality of image frames described above.

S301. The image processing apparatus acquires a reference value of a target parameter of a previous adjacent frame of the image frame to be processed.

The target parameter is used to characterize the display content performance indicator of the image frame.

It is easy to understand that if the image frame to be processed is the first image frame among the plurality of image frames, the image processing apparatus cannot acquire the reference value.

After obtaining the code stream corresponding to the plurality of image frames, the image processing device adjusts the dynamic range and color of each image frame in the code stream one by one. When the image processing apparatus performs the adjustment of the dynamic range and color of the image frame to be processed, the image processing apparatus has adjusted the dynamic range and color of the previous adjacent frame of the image frame to be processed, and therefore, the image processing apparatus can directly acquire the to-be-processed The reference value of the target parameter of the previous adjacent frame of the image frame.

The parameter value of the target parameter of the previous adjacent image frame of the image frame to be processed is substantially: the image processing device calculates the image frame to be processed before adjusting the dynamic range and color of the previous image frame of the image frame to be processed. The updated statistical value of the target parameter of the previous adjacent image frame. For ease of understanding, the present application is expressed by reference values.

S302. The image processing apparatus calculates a statistical value of a target parameter of the image frame to be processed according to the pixel value of the acquired image frame.

Here, the pixel value of the acquired image frame may be the pixel value of the image frame to be processed.

Optionally, in the case that the image processing device processes the obtained code stream in real time, if the image frame to be processed includes more pixels, the image processing device calculates the statistical value of the target parameter of the image frame to be processed in real time. For a long time, it is easy to have a delay. If the image frame to be processed includes few pixels, the image processing device can calculate the statistical data of the image frame to be processed in time. In order to avoid the delay problem, when the image frame to be processed is the t-th image frame among the plurality of image frames, the image processing apparatus calculates the ti image according to the pixel value of the tith image frame in the plurality of image frames. The target parameter of the frame, and the target parameter of the ti image frame is used as the statistical value of the target parameter of the image frame to be processed, t is a non-negative integer, and i is a positive integer.

The target parameters in the embodiment of the present application include a maximum brightness value of the display content, a maximum image average brightness value of the display content, a maximum value of the nonlinear brightness component of the display content, a minimum value of the nonlinear brightness component of the display content, an average value of the nonlinear brightness component of the display content, and a display. At least one of a content nonlinear luminance component standard variance value, a display content nonlinear luminance scaling quantization, a display content nonlinear luminance gamma value, and a display content nonlinear chrominance scaling quantization. The non-linear luminance components of the display content involved in the embodiments of the present application are both used to represent the non-linear Y component of the display content, and the non-linear chrominance components of the display content are used to represent the non-linear Cb/Cr component of the display content.

For a clearer understanding of the present application, the above parameters are now explained.

Displays the maximum brightness value of the content, which is used to indicate the maximum brightness of the displayed content. In the embodiment of the present application, the maximum brightness value of the display content is represented by Max_Content_Light_Level, and the Max_Content_Light_Level is a 16-bit unsigned integer ranging from 1 cd/m ² to 65535 cd/m ² .

Specifically, the value of Max_Content_Light_Level is the maximum value of the maximum brightness (Picture_Max_Light_Level) of all display images of a certain display content.

For a certain display image, the Picture_Max_Light_Level of the display image is calculated by calculating red (Red, R), green (Green, G), blue (for each pixel in the effective display area of the display image) The maximum value maxRGB of the Blue, B) component, the value of Picture_Max_Light_Level of the display image is equal to the maximum value of maxRGB of all the pixels in the effective display area of the display image. Here, the effective display area refers to an effective display area of the display device.

The method for calculating the maximum value maxRGB of the R, G, and B components of each pixel in the effective display area of the display image is: converting the nonlinear (R', G', B') values of the pixel points into linear The (R, G, B) value is calibrated to a value of 1 cd/m ² ; the maximum value maxRGB of the pixel R, G, and B components is calculated from the (R, G, B) values after pixel calibration.

The maximum image average brightness of the displayed content is used to indicate the maximum image average brightness of the displayed content. In the embodiment of the present application, the maximum image average brightness of the display content is represented by Max_Picture_Average_Light_Level, and the Max_Picture_Average_Light_Level is a 16-bit unsigned integer ranging from 1 cd/m 2 to 65535 cd/m ² .

Specifically, the value of Max_Picture_Average_Light_Level is the maximum value of the image average brightness Picture_Average_Light_Level of all display images of a certain display content.

For a certain display image, the calculation method of the Picture_Average_Light_Level of the display image is: calculating the maximum value maxRGB of the R, G, and B components of each pixel in the effective display area of the display image, and the Picture_Max_Light_Level of the display image The value is equal to the average of the maxRGB of all the pixels in the effective display area of the display image.

Display the maximum value of the nonlinear component of the content, indicating the nonlinearity of the pixel of the displayed content (R', G', The maximum value of the nonlinear Y' component after the B') value is converted to a non-linear (Y', Cb, Cr) value. In the embodiment of the present application, content_Nonlinear_Max_Luminance is used to represent the maximum value of the nonlinear luminance component of the display content, and Content_Nonlinear_Max_Luminance is a 16-bit unsigned integer, which is in units of 1.0/65535, and the value ranges from 0 to 1.

Display the minimum value of the nonlinear component of the content, indicating that the nonlinear (R', G', B') value of the pixel of the display content is converted to a nonlinear (Y', Cb, Cr) value, and the nonlinear Y' component The minimum value. In the embodiment of the present application, Content_Nonlinear_Min_Luminance is used to indicate the minimum value of the nonlinear luminance component of the display content, and Content_Nonlinear_Min_Luminance is a 16-bit unsigned integer, which is in units of 1.0/65535, and the value ranges from 0 to 1.

Displaying the average value of the nonlinear component of the content, indicating that the nonlinear (R', G', B') value of the pixel of the display content is converted to a nonlinear (Y', Cb, Cr) value, and the nonlinear Y' component average of. In the embodiment of the present application, Content_Nonlinear_Average_Luminance is used to represent the average value of the nonlinear luminance component of the display content, and Content_Nonlinear_Average_Luminance is a 16-bit unsigned integer, which is in units of 1.0/65535, and the value ranges from 0 to 1.

Display the nonlinear variance of the component Y component, indicating that the nonlinear (R', G', B') value of the pixel of the display content is converted to a nonlinear (Y', Cb, Cr) value, and the nonlinear Y' component Standard variance. In the embodiment of the present application, content_Nonlinear_Variance_Luminance is used to represent the average value of the nonlinear luminance component of the display content, and Content_Nonlinear_Variance_Luminance is a 16-bit unsigned integer, which is in units of 1.0/65535, and the value ranges from 0 to 1.

The display content is non-linear luminance scaling quantization, indicating whether the nonlinear Y' component of the pixel of the display content is quantized by luminance scaling. The embodiment of the present application uses Content_Nonlinear_Scaling_Luminance to represent the non-linear luminance scaling quantization of the display content. Exemplarily, the value of Content_Nonlinear_Scaling_Luminance is 1, indicating that the pixel is subjected to luminance scaling quantization, and the value of Content_Nonlinear_Scaling_Luminance is 0, indicating that the pixel is not subjected to luminance scaling quantization.

The display content is non-linear chrominance scaling quantization, indicating whether the nonlinear Y' component of the pixel of the display content is subjected to chrominance scaling quantization. The embodiment of the present application uses Content_Nonlinear_Scaling_Chrominance to represent the non-linear chrominance scaling quantization of the display content. Exemplarily, the value of Content_Nonlinear_Scaling_Chrominance is 1, indicating that the pixel is subjected to chrominance scaling quantization, and the value of Content_Nonlinear_Scaling_Chrominance is 0, indicating that the pixel is not subjected to chrominance scaling quantization.

A non-linear luminance gamma value is displayed, which represents a non-linear Y' component of the pixel of the displayed content, and a quantized gamma value. The embodiment of the present application uses Content_Nonlinear_Scaling_Gamma to represent the non-linear luminance gamma value of the display content, and Content_Nonlinear_Scaling_Gamma is an 8-bit unsigned integer in units of 1.0/128.

S303. The image processing apparatus calculates an absolute value of a difference between the reference value in the above S301 and the statistical value in the above S302.

Illustratively, if the above absolute value is represented by x, the above reference value is represented by M _t-1 , and C _t represents the above statistical value, then x=|M _t-1 -C _t |.

S304. The image processing device calculates the update coefficient by using the hyperbolic tangent function based on the absolute value calculated in S303.

Optionally, the hyperbolic tangent function in the embodiment of the present application is as shown in formula (1):

Where A is the update coefficient, x is the above absolute value, a is the first preset value, and b is the second preset value. The image processing apparatus can calculate the update coefficient based on the above formula.

Exemplarily, when a=3, b=0.5, the hyperbolic tangent function in the embodiment of the present application is as shown in formula (2):

Fig. 4 shows the curve of the above formula (2). As can be seen from Fig. 4, the hyperbolic tangent function has a monotonous increase, and the change characteristic of the curve is that the both ends are more intense and the middle is gentle. When the value of the independent variable x of the above formula (2) is small, the value of the dependent variable A is also small; when the value of the independent variable x is large, the value of the dependent variable A is also large. Since the argument x of the function represents the above absolute value, the value of the argument x can indirectly indicate whether a scene switch occurs between the image frame to be processed and the previous adjacent frame of the image frame to be processed. Generally, if the scenes of two adjacent image frames are different, the difference between the statistical values of the target parameters of the two image frames is large. The hyperbolic tangent function is used to calculate the update coefficient. In the case where the absolute value is large, the image processing apparatus can also acquire a large update coefficient, so that the image processing apparatus can quickly update the target parameter of the image frame to be processed. Statistics.

S305. The image processing apparatus calculates an updated statistical value of the target parameter of the image frame to be processed by using the time domain filter function according to the update coefficient, the reference value, and the statistical value.

When the image frame to be processed is the t-th image frame of the plurality of image frames, t=0, the image frame to be processed is the first image frame of the plurality of image frames.

As can be seen from the foregoing description, when the image frame to be processed is the first image frame of the plurality of image frames, the image processing apparatus cannot acquire the reference value. Specifically, when the image frame to be processed is the first image frame of the plurality of image frames, the image processing apparatus may determine that the updated statistical value of the target parameter of the image frame to be processed is C ₀ . Wherein C ₀ is a fourth preset value, or C ₀ is obtained by the image processing device by parsing the code stream.

Exemplarily, the image processing apparatus determines that the updated statistical value C ₀ of the target parameter of the image frame to be processed is: Max_Content_Light_Level=10000 cd/m ² , Max_Picture_Average_Light_Level=90 cd/m ² , Content_Nonlinear_Max_Luminance=65535, Content_Nonlinear_Min_Luminance=0, Content_Nonlinear_Average_Luminance=17000 Content_Nonlinear_Variance_Luminance=8500, Content_Nonlinear_Scaling_Luminance=0, Content_Nonlinear_Scaling_Chrominance=0, Content_Nonlinear_Scaling_Gamma=128.

When the image frame to be processed is the t-th image frame of the plurality of image frames, when t>0, the image processing apparatus calculates the updated statistical value M _t of the target parameter of the image frame to be processed by using the following formula (3):

M _t =A×C _t +B×M _t-1 (3)

Where A is the above update coefficient, C _t is the statistical value of the target parameter of the image frame to be processed, B is the third preset value, and M _t-1 is the reference of the target parameter of the previous adjacent frame of the image frame to be processed. value.

Optionally, in the above formula (3), B=1-A. In this way, the image processing apparatus can perform weighting according to the update coefficient in time, and more accurately calculate the updated statistical value M _t of the target parameter of the image frame to be processed.

S306. The image processing apparatus calculates a display adaptation parameter of the image frame to be processed according to the updated statistical value of the target parameter of the image frame to be processed.

The display adaptation parameters are used to adjust the dynamic range and color of the image frame to be processed.

S307. The image processing apparatus adjusts the image frame to be processed according to the display adaptation parameter.

After the image processing device calculates the updated statistical value of the target parameter of the image frame to be processed, according to the calculation The updated statistical value completes the adjustment of the dynamic range and color of the image frame to be processed. The method for the image processing device to calculate the display adaptation parameter of the image frame to be processed according to the updated statistical value of the target parameter of the image frame to be processed may refer to the existing method for calculating the display adaptation parameter, and details are not described herein again.

S308. The image processing apparatus acquires the adjusted image frame to be processed, and sends the adjusted image frame to be processed to the display device.

S309. The display device displays the adjusted image frame to be processed.

In summary, the image processing apparatus in the embodiment of the present application calculates the absolute value of the difference between the reference value and the statistical value in real time, and calculates the update coefficient by using the hyperbolic tangent function according to the absolute value. Since the hyperbolic tangent function has a monotonous increment, and the change characteristic of the curve is that the two ends are relatively sharp and the middle is gentle, the image processing apparatus can also obtain an appropriate update coefficient when the absolute value is large, so that The image processing device can quickly update the statistical value of the target parameter of the image frame to be processed, realize the synchronization between the statistical value of the target parameter of the image frame to be processed and the adjusted image frame to be processed, and effectively solve the problem of image delay, and It will not cause the image to flicker because the update value is too large, which effectively avoids the problem of image flicker.

After the image processing device obtains the code stream corresponding to the plurality of image frames, the dynamic range and color of each image frame are adjusted, and the target parameters carried by the code stream are not adjusted. The target parameter carried by the code stream is calculated by the image processing device according to the pixel values of all image frames in the code stream, and corresponds to all the image frames in the code stream, and is used for characterizing the display content performance index of all image frames in the code stream. The target parameter carried by the code stream is static data, and the target parameter corresponds to all image frames before adjustment. When the image processing apparatus adjusts the dynamic range and color of each image frame and does not update the target parameter carried by the code stream, the target parameter carried by the code stream stored by the image processing apparatus does not match the adjusted image frame. In order to match the target parameter carried by the code stream stored by the image processing device with the adjusted image frame, the image processing device also needs to adaptively update the target parameter carried by the stored code stream, and send the updated target parameter to the display device. The display device is further adapted to adjust the dynamic range and color of the image frame according to the updated target parameter, so that the display of the image is more clear and perfect.

Specifically, as shown in FIG. 5, the image processing method provided by the embodiment of the present application includes:

S501. The image processing device acquires display parameters of the display device.

The image processing device can acquire display parameters of the display device by communicating with the display device. The display parameter includes the maximum display brightness value Max_Display_Target_Luminance of the display device.

S502. The image processing device obtains a code stream corresponding to the plurality of image frames, and acquires a target parameter from the code stream.

Here, the target parameters in this embodiment are used to characterize the display content performance indicators of all image frames. In general, the target parameter obtained from the code stream may also be referred to as metadata acquired from the code stream.

The target parameter in this embodiment includes a display content maximum brightness value Max_Content_Light_Level, and may also include a display content maximum image average brightness value, a display content nonlinear brightness component maximum value, a display content nonlinear brightness component minimum value, and a display content nonlinear brightness component. The average value, the display content nonlinear luminance component standard variance value, the display content nonlinear luminance scaling quantization, the display content nonlinear chrominance scaling quantization, and the display content nonlinear luminance gamma value.

The maximum brightness value of the display content, the maximum image average brightness value of the display content, the maximum value of the nonlinear brightness component of the display content, the minimum value of the nonlinear brightness component of the display content, the average value of the nonlinear brightness component of the display content, and the nonlinearity of the display content in this embodiment The luminance component standard variance value, the display content nonlinear luminance scaling quantization, the display content nonlinear chrominance scaling quantization, and the display content nonlinear luminance gamma value can be referred to in the embodiment shown in FIG. As described above, detailed descriptions are not repeated here.

Different from the embodiment shown in FIG. 4, the target parameter in this embodiment is a statistical value calculated by the image processing apparatus according to pixel values of all image frames in the code stream, and in the embodiment shown in FIG. The target parameter is calculated by the image processing device based on the pixel value of one image frame.

S503. The image processing apparatus calculates an adjustment coefficient according to the display parameter and the target parameter.

The adjustment coefficients include a linear domain adjustment coefficient and a nonlinear domain adjustment coefficient.

Specifically, the image processing apparatus calculates the linear domain adjustment coefficient using the following formula:

Linear_adjust_factor

=min(1.0,Max_Display_Target_Luminance/Max_Content_Light_Level)

Where min(1.0, Max_Display_Target_Luminance/Max_Content_Light_Level) represents the minimum value of 1.0 and Max_Display_Target_Luminance/Max_Content_Light_Level, and the linear_adjust_factor is a linear domain adjustment coefficient.

S504. The image processing apparatus updates the target parameter acquired in S502 according to the adjustment coefficient.

Specifically, the image processing device multiplies the maximum brightness value of the display content by the linear domain adjustment coefficient, and quantizes it into a 16-bit unsigned integer to obtain an updated maximum brightness value of the display content.

When the target parameter acquired by the image processing device includes the maximum image average brightness value of the display content, the image processing device multiplies the maximum image average brightness value of the display content by the linear domain adjustment coefficient, and quantizes to a 16-bit unsigned integer. The updated image maximum brightness value of the displayed content is obtained.

When the target parameter acquired by the image processing device includes a maximum value of the display content nonlinear luminance component, the image processing device multiplies the maximum value of the display content nonlinear luminance component by the nonlinear domain adjustment coefficient, and quantizes to 16 bits without The symbolic integer gives the maximum value of the non-linear luminance component of the updated display content.

When the target parameter acquired by the image processing device includes a minimum value of the non-linear luminance component of the display content, the image processing device multiplies the minimum value of the nonlinear luminance component of the display content by the nonlinear domain adjustment coefficient, and quantizes to 16 bits without The symbolic integer gives the minimum value of the non-linear luminance component of the updated display content.

When the target parameter acquired by the image processing device includes the average value of the non-linear luminance component of the display content, the image processing device multiplies the average value of the nonlinear luminance component of the display content by the nonlinear domain adjustment coefficient, and quantizes to 16 bits without A symbolic integer that yields an average of the non-linear luminance components of the updated display content.

When the target parameter acquired by the image processing device includes a standard variance value of the display content nonlinear luminance component, the image processing device multiplies the standard content variance value of the display content nonlinear luminance component by the nonlinear domain adjustment coefficient, and quantizes For a 16-bit unsigned integer, the updated display component nonlinear luminance component standard variance value is obtained.

When the target parameter acquired by the image processing apparatus includes the display content nonlinear brightness scaling quantization, the image processing apparatus sets the numerical value of the display content nonlinear brightness scaling quantization to a first preset threshold. Exemplarily, the first preset threshold is 0.

When the target parameter acquired by the image processing device includes non-linear chrominance scaling quantization of the display content, the image The processing device sets the numerical value of the display content nonlinear chromaticity scaling quantization to a second preset threshold. Exemplarily, the second preset threshold is zero.

When the target parameter acquired by the image processing apparatus includes the display content nonlinear luminance gamma value, the image processing apparatus sets the value of the display content nonlinear luminance gamma value to a third preset threshold. Exemplarily, the third preset threshold is 128.

S505. The image processing apparatus sends the updated target parameter to the display device.

S506. The display device adjusts a dynamic range and a color of the image frame according to the updated target parameter.

In summary, the image processing method provided by the embodiment of the present application can ensure the matching between the target parameter carried by the code stream stored by the image processing device and the adjusted image frame.

After obtaining the code stream corresponding to the plurality of image frames, the image processing device adjusts the dynamic range and color of each image frame, and the image processing device calculates the update coefficient according to the display parameters of the display device by executing the above S500-S504, and uses the update. The coefficient updates the target parameter carried by the code stream, such that the updated target parameter is adapted to the display parameters of the display device. Correspondingly, the image processing apparatus performs the above S505, that is, the target parameter carried by the code stream sent by the image processing apparatus to the display device is the target parameter updated by the image processing apparatus. The display device performs the above S506 to directly adjust the dynamic range and color of each image frame by using the updated target parameter, so that the display device not only makes the display device display the adjusted image frame more clearly and comprehensively, but also improves the display device. Performance.

An embodiment of the present application provides an image processing apparatus for performing the steps performed by the image processing apparatus in the above image processing method. The image processing apparatus provided by the embodiment of the present application may include a module corresponding to the corresponding step.

The embodiment of the present application may divide the function module into the image processing device according to the above method example. For example, each function module may be divided according to each function, or two or more functions may be integrated into one processing module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. The division of modules in the embodiments of the present application is schematic, and is only a logical function division, and may be further divided in actual implementation.

In the case where the respective functional modules are divided by the respective functions, FIG. 6 shows a possible structural diagram of the image processing apparatus involved in the above embodiments. As shown in FIG. 6, the image processing apparatus 600 includes an acquisition unit 60, a calculation unit 61, an adjustment unit 62, an update unit 63, a transmission unit 64, and a determination unit 65. The obtaining unit 60 is configured to support the image processing apparatus 600 to execute S300, S301, S325, S501, S502, etc. in the above embodiments, and/or other processes for the techniques described herein; the computing unit 61 is configured to support the image The processing device 600 performs S302, S303, S304, S305, S306, S503, etc. in the above embodiments, and/or other processes for the techniques described herein; the adjustment unit 62 is configured to support the image processing device 600 to perform the above-described implementation S307, etc. in the example, and/or other processes for the techniques described herein; an update unit 63 for supporting the image processing device 600 to perform S504, etc. in the above-described embodiments, and/or for the techniques described herein Other processes; the transmitting unit 64 is configured to support the image processing apparatus 600 to perform S308, S505, etc. in the above embodiments, and/or other processes for the techniques described herein; the determining unit 65 is configured to support the image processing apparatus 600, using the target parameter of the tith image frame calculated by the above calculating unit 61 as a statistical value of the target parameter of the image frame to be processed, and the like, and/or for the technique described herein Process. Wherein, the above method is implemented All the related content of each step involved in the example can be referred to the function description of the corresponding function module, and details are not described herein again. Of course, the image processing apparatus 600 provided by the embodiment of the present application includes but is not limited to the above modules. For example, the image processing apparatus 600 may further include a storage unit 66. The storage unit 66 can be used to store program codes and data of the image processing apparatus.

The calculation unit 61, the adjustment unit 62, the update unit 63, and the determination unit 65 in the embodiment of the present application may be the processor 21 in FIG. 2, and the acquisition unit 60 and the transmission unit 64 may be diagrams. In the input unit 24 of 2, the storage unit 66 may be the memory 23 in FIG.

When the image processing apparatus operates, the image processing apparatus executes the image processing method of the embodiment as shown in FIG. 3 or 5. For a specific image processing method, refer to the related description in the foregoing embodiment shown in FIG. 3 or FIG. 5, and details are not described herein again.

Another embodiment of the present application further provides a computer storage medium, where the computer program code is stored, when the processor 71 in the image processing device executes the program code, the image processing device executes as shown in FIG. 3 or The image processing method shown in FIG.

In another embodiment of the present application, there is also provided a computer program product comprising computer executed instructions stored in a computer readable storage medium; at least one processor of the image processing apparatus is The computer readable storage medium reads the computer to execute instructions, and the at least one processor executes the computer to execute the instructions such that the image processing apparatus implements the steps of performing the image processing apparatus in the image processing method illustrated in FIG. 3 or 5.

Through the description of the above embodiments, those skilled in the art can clearly understand that for the convenience and brevity of the description, only the division of the above functional modules is illustrated. In practical applications, the above functions can be allocated according to needs. It is completed by different functional modules, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. For the specific working process of the system, the device and the unit described above, reference may be made to the corresponding process in the foregoing method embodiments, and details are not described herein again.

In the several embodiments provided by the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be used. Combinations can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may contribute to the prior art or all or part of the technical solution may be in the form of a software product. Formally embodied, the computer software product is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to perform the methods described in various embodiments of the present application. All or part of the steps. The foregoing storage medium includes: a flash memory, a mobile hard disk, a read only memory, a random access memory, a magnetic disk, or an optical disk, and the like, which can store program codes.

The foregoing is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present application should be covered by the scope of the present application. . Therefore, the scope of protection of the present application should be determined by the scope of the claims.

Claims

An image processing method, comprising:

Obtaining a reference value of a target parameter of a previous adjacent frame of the image frame to be processed, where the target parameter is used to represent a display content performance indicator of the image frame;

Calculating a statistical value of the target parameter of the image frame to be processed according to the pixel value of the acquired image frame;

Calculating an absolute value of a difference between the reference value and the statistical value;

Calculating an update coefficient using a hyperbolic tangent function according to the absolute value;

Calculating, according to the update coefficient, the reference value, and the statistical value, an updated statistical value of a target parameter of the image frame to be processed by using a time domain filter function;

And displaying, according to the updated statistical value, a display adaptation parameter of the image frame to be processed, where the display adaptation parameter is used to adjust a dynamic range and a color of the image frame to be processed;

And adjusting the image frame to be processed according to the display adaptation parameter.
The method according to claim 1, wherein the calculating the update coefficient by using the hyperbolic tangent function according to the absolute value comprises:

The update coefficient is calculated according to the following formula:

Where A is the update coefficient, x is the absolute value, a is a first preset value, and b is a second preset value.
The method according to claim 1 or 2, wherein the method further comprises: obtaining a code stream corresponding to the plurality of image frames, wherein the image frame to be processed is in a plurality of image frames corresponding to the code stream The tth image frame, t is a non-negative integer;

And calculating, according to the update coefficient, the reference value, and the statistic value, the updated statistic value of the target parameter of the image frame to be processed by using a time domain filter function, specifically:

The updated statistical value M t is calculated using the following formula:

When t>0, M t =A×C t +B×M t-1 ;

When t=0, M t =C 0 ;

A is the update coefficient, C t is the statistical value, B is a third preset value, M t-1 is the reference value, C 0 is a fourth preset value, or C 0 is passed. Parsing the code stream is obtained.
The method of claim 3 wherein B = 1 - A.
The method according to claim 3, wherein the calculating the statistical value of the target parameter of the image frame to be processed according to the pixel value of the acquired image frame comprises:

Calculating a target parameter of the t-ith image frame according to a pixel value of the t-ith image frame in the plurality of image frames, where i is a positive integer;

The target parameter of the t-ith image frame is used as a statistical value of a target parameter of the image frame to be processed.
A method according to any one of claims 1 to 5, characterized in that

The target parameter includes a maximum brightness value of the display content, a maximum image average brightness value of the display content, a maximum value of the nonlinear brightness component of the display content, a minimum value of the nonlinear brightness component of the display content, an average value of the nonlinear brightness component of the display content, and a nonlinear display content. At least one of a luminance component standard variance value, a display content nonlinear luminance scaling quantization, a display content nonlinear luminance gamma value, and a display content nonlinear chrominance scaling quantization.
An image processing method, comprising:

Obtaining display parameters of the display device;

Obtaining a target parameter from a code stream, where the target parameter is used to represent a display content performance indicator of all image frames in the code stream;

Calculating an adjustment coefficient according to the display parameter and the target parameter;

Updating the target parameter according to the adjustment coefficient;

And transmitting, to the display device, the updated target parameter, so that the display device adjusts a dynamic range and a color of the image frame according to the updated target parameter.
The method according to claim 7, wherein the display parameter comprises a maximum display brightness value of the display device, the target parameter comprises a display content maximum brightness value, and the adjustment coefficient comprises a linear domain adjustment coefficient and a non- Linear domain adjustment factor,

And calculating, according to the display parameter and the target parameter, an adjustment parameter, including:

And calculating the linear domain adjustment coefficient according to the maximum brightness value of the display content and the maximum display brightness value of the display device by using the following formula:

Linear_adjust_factor

=min(1.0,Max_Display_Target_Luminance/Max_Content_Light_Level)

The linear_adjust_factor is the linear domain adjustment coefficient, Max_Display_Target_Luminance is the maximum display brightness value of the display device, Max_Content_Light_Level is the maximum brightness value of the display content, and min(1.0, Max_Display_Target_Luminance/Max_Content_Light_Level) indicates the minimum of 1.0 and Max_Display_Target_Luminance/Max_Content_Light_Level. value;

And calculating the nonlinear domain adjustment coefficient according to the maximum brightness value of the display content and the maximum display brightness value of the display device by using the following formula:

Wherein, the nonlinear_adjust_factor is the nonlinear domain adjustment coefficient, and the OETF (·) represents the photoelectric conversion function.
The method according to claim 8, wherein the target parameter further comprises a display content maximum image average brightness value, a display content nonlinear brightness component maximum value, a display content nonlinear brightness component minimum value, and a display content nonlinear brightness. At least one of a component average value, a display content nonlinear luminance component standard variance value, a display content nonlinear luminance scaling quantization, a display content nonlinear luminance gamma value, and a display content nonlinear chrominance scaling quantization;

Updating the target parameter according to the adjustment coefficient, specifically:

And multiplying the linear domain adjustment coefficient by the maximum brightness value of the display content, and quantizing to an unsigned integer, to obtain an updated maximum brightness value of the display content;

And when the target parameter includes the maximum image average brightness value of the display content, multiplying the linear domain adjustment coefficient by the maximum image average brightness value of the display content, and quantizing into an unsigned integer to obtain an updated display content. Maximum image average brightness value;

And when the target parameter includes the display content non-linear luminance component maximum value, multiplying the nonlinear domain adjustment coefficient by the display content nonlinear luminance component maximum value, and quantizing to an unsigned integer, and obtaining an update The maximum content of the nonlinear brightness component of the displayed content;

When the target parameter includes the display content non-linear luminance component minimum value, the nonlinear domain adjustment coefficient is multiplied by the display content nonlinear luminance component minimum value, and quantized into an unsigned integer, and obtained after updating The display content is the minimum value of the nonlinear luminance component;

When the target parameter includes the display content non-linear luminance component average value, the nonlinear domain adjustment coefficient is multiplied by the display content nonlinear luminance component average value, and quantized into an unsigned integer, and obtained after updating The display content is the average of the nonlinear luminance components;

When the target parameter includes the display content nonlinear luminance component standard variance value, multiplying the nonlinear domain adjustment coefficient by the display content nonlinear luminance component standard variance value, and quantizing to an unsigned integer Obtaining a standard deviation value of the non-linear luminance component of the updated display content;

When the target parameter includes the display content nonlinear brightness scaling quantization, setting the numerical value of the display content nonlinear brightness scaling quantization to a first preset threshold;

When the target parameter includes the display content nonlinear chrominance scaling quantization, setting the numerical value of the display content nonlinear chrominance scaling quantization to a second preset threshold;

When the target parameter includes the display content non-linear luminance gamma value, the value of the display content non-linear luminance gamma value is set to a third preset threshold.
An image processing apparatus, comprising:

And an acquiring unit, configured to acquire a plurality of image frames, and obtain reference values of target parameters of a previous adjacent frame of the image frame to be processed in the plurality of image frames, where the target parameter is used to represent performance performance of the image frame index;

a calculating unit, configured to calculate a statistic value of the target parameter of the image frame to be processed according to the pixel value of the acquired image frame acquired by the acquiring unit, and calculate the reference value acquired by the acquiring unit An absolute value of a difference from the statistical value, and for calculating an update coefficient using the hyperbolic tangent function according to the absolute value, and for using the update coefficient, the reference value, and the statistical value, Calculating, by using a time domain filter function, an updated statistical value of the target parameter of the image frame to be processed, and calculating a display adaptation parameter of the image frame to be processed according to the updated statistical value, Displaying adaptation parameters for adjusting a dynamic range and color of the image frame to be processed;

And an adjusting unit, configured to adjust the image frame to be processed according to the display adaptation parameter calculated by the calculating unit.
The image processing device according to claim 10, wherein the calculating unit is specifically configured to:

The update coefficient is calculated according to the following formula:

Where A is the update coefficient, x is the absolute value, a is a first preset value, and b is a second preset value.
The image processing device according to claim 10 or 11, wherein

The acquiring unit is further configured to obtain a code stream corresponding to the plurality of image frames, where the to-be-processed image frame is the t-th image frame of the plurality of image frames corresponding to the code stream, and t is a non-negative integer;

The calculating unit is specifically configured to: calculate the updated statistical value M t by using the following formula:

When t>0, M t =A×C t +B×M t-1 ;

When t=0, M t =C 0 ;

A is the update coefficient, C t is the statistical value, B is a third preset value, M t-1 is the reference value, C 0 is a fourth preset value, or C 0 is passed. Parsing the code stream is obtained.
The image processing device according to claim 12, wherein B = 1 - A.
The image processing device according to claim 12, wherein

The calculating unit is further configured to calculate, according to a pixel value of the t-ith image frame in the plurality of image frames, a target parameter of the t-ith image frame, where i is a positive integer;

The image processing apparatus further includes a determining unit,

The determining unit is configured to use a target parameter of the t-ith image frame calculated by the calculating unit as a statistical value of a target parameter of the image frame to be processed.
An image processing apparatus according to any one of claims 10 to 14, wherein

The target parameter includes a maximum brightness value of the display content, a maximum image average brightness value of the display content, a maximum value of the nonlinear brightness component of the display content, a minimum value of the nonlinear brightness component of the display content, an average value of the nonlinear brightness component of the display content, and a nonlinear display content. At least one of a luminance component standard variance value, a display content nonlinear luminance scaling quantization, a display content nonlinear luminance gamma value, and a display content nonlinear luminance scaling quantization.
An image processing apparatus, comprising:

An obtaining unit, configured to acquire display parameters of the display device, and configured to acquire target parameters from the code stream, where the target parameters are used to represent display content performance indicators of all image frames in the code stream;

a calculating unit, configured to calculate an adjustment coefficient according to the display parameter and the target parameter acquired by the acquiring unit;

And an updating unit, configured to update the target parameter acquired by the acquiring unit according to the adjustment coefficient calculated by the calculating unit;

And a sending unit, configured to send, to the display device, the updated target parameter obtained by the updating unit, so that the display device adjusts a dynamic range and a color of the image frame according to the updated target parameter.
The image processing device according to claim 16, wherein the display parameter comprises a maximum display brightness value of the display device, the target parameter comprises a display content maximum brightness value, and the adjustment coefficient comprises a linear domain adjustment coefficient. And nonlinear domain adjustment coefficients,

The calculating unit is specifically configured to:

And calculating the linear domain adjustment coefficient according to the maximum brightness value of the display content and the maximum display brightness value of the display device by using the following formula:

Linear_adjust_factor

=min(1.0,Max_Display_Target_Luminance/Max_Content_Light_Level)

The linear_adjust_factor is the linear domain adjustment coefficient, Max_Display_Target_Luminance is the maximum display brightness value of the display device, Max_Content_Light_Level is the maximum brightness value of the display content, and min(1.0, Max_Display_Target_Luminance/Max_Content_Light_Level) indicates the minimum of 1.0 and Max_Display_Target_Luminance/Max_Content_Light_Level. value;

And calculating the nonlinear domain adjustment coefficient according to the maximum brightness value of the display content and the maximum display brightness value of the display device by using the following formula:

Wherein, the nonlinear_adjust_factor is the nonlinear domain adjustment coefficient, and the OETF (·) represents the photoelectric conversion function.
The image processing device according to claim 17, wherein the target parameter further comprises: a display content maximum image average brightness value, a display content nonlinear brightness component maximum value, a display content nonlinear brightness component minimum value, and display content At least one of a nonlinear luminance component average value, a display content nonlinear luminance component standard variance value, a display content nonlinear luminance scaling quantization, a display content nonlinear luminance gamma value, and a display content nonlinear luminance scaling quantization;

The update unit is specifically configured to:

And multiplying the linear domain adjustment coefficient by the maximum brightness value of the display content, and quantizing to an unsigned integer, to obtain an updated maximum brightness value of the display content;

And when the target parameter includes the maximum image average brightness value of the display content, multiplying the linear domain adjustment coefficient by the maximum image average brightness value of the display content, and quantizing into an unsigned integer to obtain an updated display content. Maximum image average brightness value;

When the target parameter includes the display content non-linear luminance component maximum value, the nonlinear domain adjustment coefficient is multiplied by the display content nonlinear luminance component maximum value, and quantized into an unsigned integer, and obtained after updating The display content has a maximum nonlinear luminance component;

When the target parameter includes the display content non-linear luminance component minimum value, the nonlinear domain adjustment coefficient is multiplied by the display content nonlinear luminance component minimum value, and quantized into an unsigned integer, and obtained after updating The display content is the minimum value of the nonlinear luminance component;

When the target parameter includes the display content non-linear luminance component average value, the nonlinear domain adjustment coefficient is multiplied by the display content nonlinear luminance component average value, and quantized into an unsigned integer, and obtained after updating The display content is the average of the nonlinear luminance components;

When the target parameter includes the display content nonlinear luminance component standard variance value, multiplying the nonlinear domain adjustment coefficient by the display content nonlinear luminance component standard variance value, and quantizing to an unsigned integer Obtaining a standard deviation value of the non-linear luminance component of the updated display content;

When the target parameter includes the display content nonlinear brightness scaling quantization, setting the numerical value of the display content nonlinear brightness scaling quantization to a first preset threshold;

When the target parameter includes the display content nonlinear chrominance scaling quantization, setting the numerical value of the display content nonlinear chrominance scaling quantization to a second preset threshold;

When the target parameter includes the display content non-linear luminance gamma value, the value of the display content non-linear luminance gamma value is set to a third preset threshold.
An image processing apparatus, comprising: one or more processors, a memory, and a communication interface;

The memory, the communication interface is coupled to the one or more processors; the image processing device is in communication with other devices via the communication interface; the memory is for storing computer program code, the computer program code comprising The image processing apparatus performs the image processing method according to any one of claims 1 to 6 or performs any one of claims 7-9 when the one or more processors execute the instructions. The image processing method described in the item.
A computer storage medium storing instructions in the computer storage medium, characterized in that The image processing device, when executed on an image processing device, causes the image processing device to perform the image processing method according to any one of claims 1 to 6 or to perform the image according to any one of claims 7-9 Approach.
A computer program product comprising instructions, wherein when the computer program product is run on an image processing device, the image processing device is caused to perform the image processing method according to any one of claims 1-6 Or the image processing method according to any one of claims 7-9.