A color dynamic compensation method based on window self-adaption and related equipment

Abstract

The application belongs to the technical field of display, and relates to a colorimetric dynamic compensation method based on window self-adaptation and related equipment, which comprises the following steps: acquiring input video data; detecting the equivalent driving window size of a current video frame image in the input video data in real time; acquiring a compensation model according to the signal type of the input video data; generating a compensation coefficient corresponding to the equivalent driving window size according to the compensation model; performing timing smoothing processing on the compensation coefficient; and performing compensation processing on the current video frame image according to the smoothed compensation coefficient to obtain a compensated video frame image. According to the application, a mapping model of window size and color temperature drift and a mapping model of window size and peak brightness are established, and the white point compensation coefficient and the EOTF / luminance mapping parameter are dynamically adjusted according to the signal type of different mini LED televisions, so that the colorimetric deviation converges to the range that cannot be perceived by the human eye under all typical window sizes, and high-consistency color performance independent of the window is realized.

Description

Technical Field

[0001] This application relates to the field of display technology, and in particular to a color accuracy dynamic compensation method and related equipment based on window adaptation. Background Technology

[0002] Mini LED TVs use thousands to tens of thousands of micron-sized LED chips as backlights, achieving high brightness and high contrast through backlight zone control.

[0003] There is a color accuracy compensation scheme that uses globally fixed compensation parameters, that is, a fixed set of compensation coefficients is uniformly applied to the entire image.

[0004] However, in practical applications, the size of the driving window (i.e., the mapping relationship between the actual lit pixel area and the driving signal) may differ in different areas, especially in scenarios with local dimming backlight, variable refresh rate, or different resolution signal inputs, where the size of the driving window will change dynamically.

[0005] It is evident that traditional methods with fixed compensation parameters cannot adapt to scenarios involving changes in window size, leading to over-compensation or under-compensation, which in turn affects overall color accuracy. Summary of the Invention

[0006] The purpose of this application is to propose a color accuracy dynamic compensation method and related equipment based on window adaptation, so as to solve the problem that the traditional fixed compensation parameter method cannot adapt to the above-mentioned scenarios of window size changes, resulting in over-compensation or under-compensation, which in turn affects the overall color accuracy performance.

[0007] To address the aforementioned technical problems, this application provides a color accuracy dynamic compensation method based on window adaptation, employing the following technical solution: Obtain input video data; Real-time detection of the equivalent driving window size of the current video frame image in the input video data; Obtain the signal type of the input video data; Read the model database and obtain the compensation model corresponding to the signal type from the model database; Based on the compensation model, compensation coefficients corresponding to the equivalent driving window size are generated; The compensation coefficients are subjected to time-series smoothing to obtain smoothed compensation coefficients; The current video frame image is compensated according to the smoothed compensation coefficient to obtain the compensated video frame image.

[0008] To address the aforementioned technical problems, this application also provides a window-adaptive color accuracy dynamic compensation device, employing the following technical solution: The input video acquisition module is used to acquire input video data; An equivalent driving window size detection module is used to detect the equivalent driving window size of the current video frame image in the input video data in real time. The management mode acquisition module is used to acquire the signal type of the input video data; The compensation model acquisition module is used to read the model database and acquire the compensation model corresponding to the signal type from the model database. The compensation coefficient generation module is used to generate compensation coefficients corresponding to the equivalent driving window size based on the compensation model. A timing smoothing module is used to perform timing smoothing on the compensation coefficients to obtain smoothed compensation coefficients. The compensation processing module is used to perform compensation processing on the current video frame image according to the smoothed compensation coefficient to obtain the compensated video frame image.

[0009] To address the aforementioned technical problems, this application also provides a computer device that employs the following technical solution: It includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor executes the computer-readable instructions to implement the steps of the window-adaptive color accuracy dynamic compensation method as described above.

[0010] To address the aforementioned technical problems, this application also provides a computer-readable storage medium, employing the technical solution described below: The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the window-adaptive color accuracy dynamic compensation method described above.

[0011] This application provides a window-adaptive dynamic color accuracy compensation method, comprising: acquiring input video data; real-time detection of the equivalent driving window size of the current video frame image in the input video data; acquiring the signal type of the input video data; reading a model database and acquiring a compensation model corresponding to the signal type in the model database; generating compensation coefficients corresponding to the equivalent driving window size according to the compensation model; performing temporal smoothing processing on the compensation coefficients to obtain smoothed compensation coefficients; and performing compensation processing on the current video frame image according to the smoothed compensation coefficients to obtain a compensated video frame image. Compared with the prior art, this application establishes a mapping model between window size and color temperature drift, and a mapping model between window size and peak brightness, and dynamically adjusts the white point compensation coefficient and EOTF / brightness mapping parameters according to different miniLED TV signal types, so that under all typical window sizes, the color accuracy deviation ΔE converges to a range imperceptible to the human eye (ΔE<1.5), achieving window-independent high-consistency color performance. Attached Figure Description

[0012] To more clearly illustrate the solutions in this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is an exemplary system architecture diagram to which this application can be applied; Figure 2 This is a flowchart illustrating the implementation of the window-adaptive color accuracy dynamic compensation method provided in this application embodiment; Figure 3 This is a schematic diagram of the color temperature drift curves under different window sizes provided in the embodiments of this application; Figure 4 This is a schematic diagram of the peak brightness curves under different window sizes provided in the embodiments of this application; Figure 5 This is a comparison chart of the accuracy of cubic spline interpolation and piecewise linear interpolation provided in the embodiments of this application; Figure 6 This is a schematic diagram of the step response curve of the IIR filter provided in the embodiments of this application; Figure 7 This is a comparison diagram of ΔE before and after compensation provided in the embodiments of this application; Figure 8 This is a schematic diagram of the structure of the color accuracy dynamic compensation device based on window adaptation provided in the embodiments of this application; Figure 9This is a schematic diagram of the structure of one embodiment of the computer device according to this application. Detailed Implementation

[0014] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.

[0015] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0016] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0017] like Figure 1 As shown, system architecture 100 may include terminal device 101, network 102, and server 103. Terminal device 101 may be a laptop 1011, tablet 1012, or mobile phone 1013. Network 102 is used as a medium to provide a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0018] Users can use terminal device 101 to interact with server 103 via network 102 to receive or send messages, etc. Various communication client applications can be installed on terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social media platform software, etc.

[0019] Terminal device 101 can be various electronic devices with a display screen and support web browsing. In addition to laptops 1011, tablets 1012, or mobile phones 1013, terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 player (Moving Picture Experts Group Audio Layer IV), a laptop computer, and a desktop computer, etc.

[0020] Server 103 can be a server that provides various services, such as a backend server that provides support for the pages displayed on terminal device 101.

[0021] It should be noted that the window-adaptive dynamic color accuracy compensation method provided in this application embodiment is generally executed by a server / terminal device, and correspondingly, the window-adaptive dynamic color accuracy compensation device is generally set in the server / terminal device.

[0022] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0023] Continue to refer to Figure 2 The diagram shows a flowchart of an embodiment of the window-adaptive dynamic color accuracy compensation method according to this application. The above-described window-adaptive dynamic color accuracy compensation method includes steps S201, S202, S203, S204, S205, S206, and S207.

[0024] In step S201, input video data is acquired.

[0025] In step S202, the equivalent driving window size of the current video frame image in the input video data is detected in real time.

[0026] In some optional implementations of the embodiments of this application, the step of real-time detection of the equivalent driving window size of the current video frame image in the input video data specifically includes the following steps: (1) Calculate the number of partitions in the current video frame and the brightness level of each partition; (2) Calculate the equivalent driving window size based on the number of partitions and the brightness level of each partition.

[0027] In this embodiment, the Mini LED TV employs numerous backlight zones to achieve high-contrast display. The actual number of illuminated zones and the distribution of driving current vary significantly depending on the content displayed. Traditional color accuracy compensation methods typically use the proportion of bright areas in the image as a window size estimate, ignoring the actual driving state of the backlight zones, resulting in insufficient compensation accuracy. Especially in small window scenarios, the error of traditional methods can reach several percentage points, directly affecting the color accuracy compensation effect. Therefore, a real-time detection method for the equivalent driving window size based on a backlight simulation algorithm is needed.

[0028] In this embodiment, the current video frame image is processed using a backlight simulation algorithm to count the number of actually lit partitions and the brightness level (driving current level) of each partition. Specifically, the application pre-establishes a one-to-one correspondence matrix between the physical partitions of the backlight module and the image pixels, clarifies the pixel range covered by each partition, performs grayscale conversion and noise reduction on the input image, extracts the brightness value of each pixel, and filters out invalid noise to avoid misjudgment. Then, for the number of partitions, the application first traverses all backlight partitions and counts the maximum brightness value of the pixels covered by the partition. If the brightness exceeds a preset threshold, it is marked as a partition to be lit. Based on the backlight diffusion model, overflow is performed on the adjacent areas of the bright partition. The calculation of the impact is as follows: if the brightness of an adjacent partition is still higher than the dark field threshold after light overflow, it is simultaneously included in the lighting range. Finally, deduplication verification is performed on all partitions marked as lit, and the total number of partitions that actually need to be lit in this scene is finally calculated. For the brightness level, this application uses the maximum brightness of the pixels in the partition as the basis, combined with the screen's Gamma curve mapping, to obtain the initial target brightness value of the partition. Then, the brightness of adjacent partitions is gradient-limited to avoid brightness jumps and blockages, while suppressing the halo overflow problem in high-brightness areas. Finally, the adjusted target brightness is matched with the actual brightness level supported by the hardware, and the brightness value that can be directly driven by each partition is finally output.

[0029] In practical applications, taking a 55-inch Mini LED TV from a certain brand as an example, the total number of backlight zones is 1152 (arranged in a 36×32 pattern). Assuming the current frame depicts a bright moon in the starry sky, with the bright area concentrated in the center of the screen covering approximately 8% of the area, then: The backlight simulation algorithm calculated the number of illuminated zones to be 92 (approximately 8% of the total 1152 zones). • Brightness levels for each zone: The 28 central zones have a maximum brightness level of 255, while the 64 outer zones have a brightness level of 150.

[0030] In this embodiment, the equivalent driving window size Weff is obtained through weighted calculation based on the number of lit zones and the brightness level of each zone:

[0031] in: N represents the actual number of zones that are illuminated; Let be the area of ​​the i-th partition; Let be the brightness level of the i-th partition; The maximum brightness level is 255.

[0032] In this embodiment of the application, taking the above-mentioned starry sky and bright moon scene as an example, the equivalent driving window size Weff is calculated to be 5.7%.

[0033] In this embodiment, the equivalent driving window size takes into account both the actual number of lit zones and the brightness distribution of each zone, which is more accurate than simply estimating based on the proportion of bright areas in the image and can accurately reflect the actual driving state of the backlight system.

[0034] Compared with existing technologies, this application calculates the number of mini LED zones actually lit in the current video frame image and the brightness level of each zone, and accurately calculates the equivalent driving window size Weff, providing accurate input parameters for subsequent color accuracy dynamic compensation, ensuring that the color accuracy deviation ΔE converges to a range imperceptible to the human eye (ΔE<1.5) under all typical window sizes.

[0035] In the embodiment of this application for real-time detection of the equivalent driving window size, the number of mini LED zones actually lit and the driving current distribution are calculated after the backlight simulation algorithm, and the equivalent driving window size Weff is calculated.

[0036] In practical applications, taking a 55-inch Mini LED TV from a certain brand as an example, the specific parameters are as follows: Number of backlight zones: 1152 (36×32); LED type: Mini LED chip, blue light chip + quantum dot film; Boost mode: supported, maximum peak brightness can reach 2000 nits; Color accuracy target: D65 (x=0.3127, y=0.3290). Taking a frame as an example, assuming the image content is a bright moon in the starry sky (the bright area is concentrated in the center of the screen, about 8% of the area), this application calculates the number of lit zones through a backlight simulation algorithm: 92 zones (out of a total of 1152), and the brightness level of each zone: the 28 central zones have a maximum brightness level of 255, and the 64 outer zones have a level of 150. The calculated equivalent driving window size Weff = 5.7%.

[0037] In step S203, the signal type of the input video data is obtained.

[0038] In this embodiment of the application, the signal types of the mini LED TV specifically include standard dynamic range mode, high dynamic range mode, and Dolby Vision mode.

[0039] In step S204, the model database is read, and the compensation model corresponding to the signal type is obtained from the model database.

[0040] In this embodiment of the application, the model database is pre-built with a window-color temperature drift feature model and a window-peak brightness feature model, specifically: ① Window-Color Temperature Drift Feature Model: Establish a lookup table or piecewise fitting function for the window size W and the white point offsets ΔCx(W) and ΔCy(W). In a laboratory darkroom environment, use a Konica Minolta CS-2000 spectroradiometer to measure the white point color coordinates under different window sizes, such as... Figure 3 The diagram shows the color temperature drift curves under different window sizes. Actual measurement data shows that when the window size is greater than 80%, the color temperature drift is negligible; starting from 50%, the color temperature drift becomes increasingly significant; the smaller the window size, the higher the color temperature (from 6500K to 7000K), and the white point coordinates drift towards the blue-violet direction.

[0041] ② Window-Peak Brightness Feature Model: Establish a lookup table or piecewise fitting function for the window size W → peak brightness L_peak(W). For example... Figure 4 The diagram shows the peak brightness curves for different window sizes, exhibiting a unimodal distribution: reaching a maximum of 2000 nits in the medium window (20%), and gradually decreasing towards both sides. In the rising segment (100%→20%), the window size decreases, power becomes more concentrated, and the peak brightness monotonically increases from 800 nits to 2000 nits; in the falling segment (20%→5%), thermal limitation and a reduction in the number of lamps cause the brightness to decrease from 2000 nits to 1700 nits.

[0042] The above model uses cubic spline interpolation for fitting. Spline interpolation, also known as cubic spline interpolation, is a process of obtaining a set of curve functions mathematically by solving a system of three moment equations through a series of shape points to obtain a smooth curve. This cubic spline interpolation ensures that C... 0 C¹ and C² are continuous, meaning that the function value, first derivative, and second derivative are all continuous, thus avoiding visual jumps, abrupt changes in the rate of change, and the perception of inflection points.

[0043] In practical applications, assume there are n measurement nodes ( , ), where i=1,...,n, Possible points Given the known function values, this application specifies the interval [ , Construct a cubic polynomial on the above:

[0044] in, This interval represents [ , The coefficient of the cubic term, This interval represents [ , The second derivative at the starting point is 1 / 2. This indicates the interval [ , The first derivative value at the starting point, This indicates the interval [ , The function value at the starting point The cubic polynomial satisfies the following boundary conditions (natural splines): C 0 continuous: = , = (The function value is continuous); C¹Continuous: = (The first derivative is continuous); C² continuity: = (The second derivative is continuous); Natural boundary conditions: =0, =0.

[0045] For the above n measurement nodes ( , First, use binary search to determine the interval in which it lies. , Then, substitute the values ​​into the cubic polynomial formula for that segment to calculate the final interpolation.

[0046] In practical applications, taking window-peak brightness mapping as an example, for Weff = 17.5% (between 15% and 20%), this application calculates the interpolation results using both cubic spline interpolation and cubic spline interpolation methods, obtaining the following results: Figure 5 The graph showing the accuracy comparison between cubic spline interpolation and piecewise linear interpolation (the upper curve represents cubic spline interpolation, and the lower curve represents piecewise linear interpolation) and the table below showing the interpolation accuracy comparison are as follows:

[0047] The comparison shows that cubic spline interpolation takes into account the curvature of the curve, which is closer to the actual physical trend, while piecewise linear interpolation only considers a simple linear average, and its accuracy is lower.

[0048] In this embodiment, different compensation strategies are adopted according to the standard dynamic range mode, high dynamic range mode, and Dolby Vision mode of the current mini LED TV signal types. Specifically: ① Standard Dynamic Range Mode: Only white point correction is performed. Specifically, the horizontal coordinate offset Δx(Weff) and vertical coordinate offset Δy(Weff) of the white point color coordinates corresponding to the equivalent driving window size of the current video frame image are calculated based on the pre-established window-color temperature drift feature model. Then, the RGB compensation coefficients are solved based on the horizontal coordinate offset Δx(Weff) and vertical coordinate offset Δy(Weff).

[0049] In some optional implementations of the embodiments of this application, when the signal type of the mini LED TV is standard dynamic range mode, the compensation model is a window-color temperature drift mapping model. The step of generating compensation coefficients corresponding to the equivalent driving window size based on the compensation model specifically includes the following steps: (1) Obtain the first color coordinate offset corresponding to the equivalent driving window size according to the window-color temperature drift mapping model; (2) Calculate the first RGB compensation coefficient based on the first color coordinate offset to obtain the compensation coefficient.

[0050] In this embodiment, the white point color temperature of a Mini LED TV experiences significant drift under different window sizes due to variations in backlight power distribution, thermal effects, and the characteristics of the mini LED chip. Especially in small window scenarios, the color temperature can rise from 6500K to 7000K, with the white point coordinates shifting towards the blue-violet direction, resulting in a color accuracy deviation ΔE as high as 6.0, far exceeding the threshold imperceptible to the human eye (ΔE < 1.5). Existing standard dynamic range mode color accuracy compensation methods mostly use fixed white balance coefficients, failing to consider the impact of window size on color temperature drift, leading to severe color accuracy degradation under small window conditions. Therefore, a method is needed to dynamically generate RGB compensation coefficients based on the equivalent driving window size.

[0051] In this embodiment, the RGB compensation coefficient is essentially the RGB white balance gain of the signal layer. Since the human eye's perception of brightness is mainly dominated by green light (~530nm), the human eye is most likely to notice deviations in green. Therefore, to keep G accurate, this application corrects the white point by adjusting the brightness ratios R and B of the three RGB channels.

[0052] In practical applications, assuming the value of Δx (5.7%) is -0.0115, the value of Δy (5.7%) is -0.0113, the target D65 standard white point is (x_target=0.3127, y_target=0.3290), and the current white point is (x_curr=0.3012, y_curr=0.3177), then by solving the RGB Gain compensation coefficient [k_R=1.015, k_G=1.000, k_B=0.982], the current white point can be adjusted by increasing the R channel brightness by 1.5%, keeping the G channel unchanged, and decreasing the B channel brightness by 1.8%, thus allowing the corrected white point to return to the target D65 standard white point.

[0053] Compared with the prior art, this application obtains the white point coordinate offset corresponding to the equivalent driving window size, calculates the RGB Gain compensation coefficient, and adjusts the brightness ratios R and B of the RGB three channels according to the RGB Gain compensation coefficient to correct the white point, so that the color accuracy deviation ΔE under all typical window sizes converges to the range imperceptible to the human eye (ΔE<1.5).

[0054] ② High Dynamic Range Mode: EOTF adaptive mapping is performed first, followed by the white point correction mentioned above. Specifically, the EOTF adaptive mapping first calculates the current peak brightness L_peak(Weff) corresponding to the equivalent driving window size of the current video frame image based on a pre-established window-peak brightness mapping model. Then, it recalculates the actual output brightness corresponding to each input code value based on the current peak brightness L_peak(Weff), generating a completely new custom PQ mapping table. This ensures that the input signal no longer uses the standard PQ's 10000 nits upper limit, but instead directly binds 100% of the maximum input signal value to the hardware peak brightness calculated through cubic spline interpolation, allowing the full-scale of the input signal to perfectly match the screen's actual maximum luminous capacity.

[0055] In some optional implementations of the embodiments of this application, when the signal type of the mini LED TV is high dynamic range mode, the compensation model is a window-color temperature drift mapping model and a window-peak brightness mapping model. The step of generating compensation coefficients corresponding to the equivalent driving window size according to the compensation model specifically includes the following steps: (1) Obtain the second color coordinate offset corresponding to the equivalent driving window size based on the window-color temperature drift mapping model; (2) Calculate the second RGB compensation coefficient based on the second color coordinate offset; (3) Obtain the first current peak brightness corresponding to the equivalent driving window size according to the window-peak brightness mapping model; (4) Obtain the PQ mapping standard parameters, and scale the PQ mapping standard parameters according to the first current peak brightness to obtain the PQ mapping compensation coefficient; (5) Use the second RGB compensation coefficient and the PQ mapping compensation coefficient as compensation coefficients.

[0056] In this embodiment, Mini LED TVs in high dynamic range mode suffer from two key problems due to changes in the screen content window size: first, the white point color temperature drifts with changes in window size (the color temperature increases from 6500K to 7000K in a small window, with ΔE reaching as high as 6.0); second, the peak brightness exhibits a single-peak distribution (reaching a peak of 2000 nits at 20% of the window and decreasing towards both sides). Existing color accuracy compensation methods for high dynamic range modes mostly use fixed PQ mapping curves, failing to consider the impact of window size on peak brightness, resulting in a mismatch between the actual brightness and the mapping target in a small window, leading to severe color accuracy degradation. Therefore, a dynamic compensation method that simultaneously performs EOTF adaptive mapping and white point correction is needed.

[0057] In this embodiment, PQ mapping is the electro-optical conversion function (EOTF) defined in the HDR (High Dynamic Range) standard, which maps digital signal values ​​to the actual brightness (unit: nit) on the screen.

[0058] In this embodiment, the standard PQ curve input range is 0-10000 nits, while the actual peak display brightness is L_peak(Weff). The PQ mapping table is scaled as follows: • Mapping target range: 0~L_peak(Weff) (instead of the standard 0~10000 nits); • Recalculate the PQ mapping table so that 100% of the input signal corresponds to the actual brightness of L_peak(Weff).

[0059] In practical applications, taking Weeff=5.7% as an example: • Original PQ curve: 0-10000 nits; • Scaled PQ curve: 0-1720 nits; • PQ mapping compensation coefficient = L_peak(Weff) / 10000 = 1720 / 10000 = 0.172.

[0060] In this embodiment, since PQ is a strongly non-linear operation and RGB Gain is a linear operation, performing non-linear operation first and then linear operation results in clean and independent effects; conversely, the effect of linear operation would be distorted by the non-linear function. Therefore, the compensation execution order is: first perform PQ mapping scaling (EOTF adaptive), then perform white point correction (RGB Gain).

[0061] Compared with the prior art, this application obtains the white point coordinate offset and the current peak brightness corresponding to the equivalent driving window size, generates RGB compensation coefficient and PQ mapping compensation coefficient respectively, and performs white point correction and peak brightness adjustment based on the RGB compensation coefficient and PQ mapping compensation coefficient, so that the color accuracy deviation ΔE under all typical window sizes converges to the range imperceptible to the human eye (ΔE<1.5).

[0062] ③ Dolby Vision Mode: First, adaptive brightness mapping is performed, followed by the white point correction mentioned above. Specifically, the adaptive brightness mapping first calculates the current peak brightness L_peak(Weff) corresponding to the equivalent driving window size of the current video frame image based on a pre-established window-peak brightness mapping model and cubic spline interpolation. Then, the display management parameters are dynamically adjusted based on the current peak brightness L_peak(Weff), and the brightness mapping curve is recalculated.

[0063] In some optional implementations of the embodiments of this application, when the signal type of the mini LED TV is Dolby Vision mode, the compensation model is a window-color temperature drift mapping model and a window-peak brightness mapping model. The step of generating compensation coefficients corresponding to the equivalent driving window size according to the compensation model specifically includes the following steps: (1) Obtain the third color coordinate offset corresponding to the equivalent driving window size based on the window-color temperature drift mapping model; (2) Calculate the third RGB compensation coefficient based on the third color coordinate offset; (3) Obtain the second current peak brightness corresponding to the equivalent driving window size according to the window-peak brightness mapping model; (4) Adjust the maximum brightness parameter of Dolby Vision mode according to the second current peak brightness to obtain the current maximum brightness; (5) Calculate the brightness mapping curve based on the current maximum brightness to obtain the adaptive brightness mapping compensation coefficient; (6) Use the third RGB compensation coefficient and the adaptive brightness mapping compensation coefficient as compensation coefficients.

[0064] In this embodiment, the Mini LED TV in Dolby Vision mode contains dynamic metadata, which needs to be mapped to brightness based on parameters such as the peak brightness value that the display device should achieve. However, due to changes in the screen window size, two key problems exist: first, the white point color temperature drifts with changes in window size (when the color temperature rises from 6500K to 7000K in a small window, ΔE can be as high as 6.0); second, the peak brightness exhibits a single-peak distribution (reaching a peak of 2000 nits at 20% of the window and decreasing towards both sides). Existing color accuracy compensation methods in Dolby Vision mode mostly use a fixed brightness mapping curve (trimpass), which does not consider the influence of window size on peak brightness, resulting in a mismatch between the actual brightness and the target maximum brightness (the peak brightness value that the display device should achieve) in the Dolby Vision metadata, leading to severe color accuracy degradation. Therefore, a dynamic compensation method that simultaneously performs brightness mapping curve adaptation and white point correction is needed. In this embodiment, the Target Max Luminance in the Dolby Vision metadata is obtained (originally based on a 100% full-screen window calibration). Taking this embodiment as an example, the original TargetMax Luminance is 800 nits (based on a 100% window).

[0065] In this embodiment, the display management parameters are dynamically adjusted based on the second current peak brightness L_peak(Weff):

[0066] In practical applications, taking Weeff=5.7% as an example:

[0067] In this embodiment, the Dolby Vision luminance mapping curve (trim pass) is recalculated to ensure that highlight details are reasonably mapped within the L_max_current range.

[0068] In this embodiment of the application, the standard Dolby Vision brightness mapping range is 0~L_max_current (instead of a fixed 0~800 nits).

[0069] Adaptive brightness mapping compensation coefficient:

[0070]

[0071] Finally, taking Weeff=5.7% as an example, the compensation coefficient is:

[0072] The compensation execution order is as follows: first, the brightness mapping curve is adapted, and then the white point correction is performed. That is, the third RGB compensation coefficient is applied to the RGB signal after brightness mapping to perform white point correction.

[0073] Compared with the prior art, this application obtains the white point coordinate offset and the current peak brightness corresponding to the equivalent driving window size through cubic spline interpolation, generates RGB compensation coefficient and adaptive brightness mapping compensation coefficient respectively, and performs white point correction and adaptive brightness adjustment according to the RGB compensation coefficient and adaptive brightness mapping compensation coefficient respectively, so that the color accuracy deviation ΔE under all typical window sizes converges to the range imperceptible to the human eye (ΔE<1.5).

[0074] In step S205, compensation coefficients corresponding to the equivalent driving window size are generated based on the compensation model.

[0075] In practical applications, taking the standard dynamic range mode and Weff=5.7% as an example: assuming the value of Δx(5.7%) is -0.0115, the value of Δy(5.7%) is -0.0113, the target D65 standard white point is (x_target=0.3127, y_target=0.3290), and the current white point is (x_curr=0.3012, y_curr=0.3177), then by solving the RGB Gain compensation coefficient [k_R=1.015, k_G=1.000, k_B=0.982], the current white point can be adjusted by increasing the R channel brightness by 1.5%, keeping the G channel unchanged, and decreasing the B channel brightness by 1.8%, thus allowing the corrected white point to return to the target D65 standard white point.

[0076] In step S206, the compensation coefficients are subjected to time-series smoothing to obtain smoothed compensation coefficients.

[0077] In this embodiment, when the compensation coefficient is an RGB compensation coefficient, a first-order IIR low-pass filter is used to perform timing smoothing on the compensation coefficient. The recursive formula for this first-order IIR low-pass filter is as follows: y[n] = α·x[n] + (1-α)·y[n-1] Where y[n] represents the output value of the current frame (the smoothed compensation coefficient), x[n] represents the input value of the current frame (the measured compensation coefficient), y[n-1] represents the output value of the previous frame, and α is the filtering coefficient. In this embodiment, α = 0.06 is taken. This value was determined through subjective experiments: the threshold of the color coordinate change rate that the human eye can perceive is 0.002 / frame. To ensure a safety margin, the target inter-frame change rate is set to ≤ 0.001 / frame. Given that the maximum abrupt change amplitude of the compensation coefficient Δk_max = 0.015, then α × 0.015 ≤ 0.001, resulting in α ≤ 0.067. Taking α = 0.06 achieves the best balance between response speed and smoothing effect. Figure 6 The diagram shows a schematic of the step response curve of an IIR filter.

[0078] In this embodiment, the IIR filter only needs to store the output of the previous frame, with low storage overhead (only 3 float variables), and only 3 multiplications and 2 additions per frame, making it suitable for real-time embedded systems.

[0079] In this embodiment, when the compensation coefficient is the PQ mapping compensation coefficient, this application smooths the peak brightness change between two adjacent frames using a smoothing ratio α=0.06. For example:

[0080] In step S207, the current video frame image is compensated according to the smoothed compensation coefficient to obtain the compensated video frame image.

[0081] In the embodiments of this application, the smoothed RGB compensation coefficients are applied to the RGB signal of the current frame image to complete white point correction and / or brightness mapping adjustment, and output the compensated video frame image.

[0082] In practical applications, taking a certain brand's 55-inch Mini LED TV as an example: it has 1152 backlight zones (36×32), uses Mini LED chips (blue light chip + quantum dot film), supports a maximum peak brightness of 2000 nits in Boost mode, and has a color accuracy target of D65 (x=0.3127, y=0.3290). This application compensates for different window sizes using smoothed RGB compensation coefficients, resulting in the following table and... Figure 7 The comparison chart of ΔE before and after compensation is shown below:

[0083] Test conclusion: After compensation, ΔE was controlled within 1.5 in all windows, reaching a level imperceptible to the human eye, and the improvement rate was most significant near the peak point (>70%).

[0084] In this application embodiment, a window-adaptive dynamic color accuracy compensation method is provided, comprising: acquiring input video data; real-time detection of the equivalent driving window size of the current video frame image in the input video data; acquiring the signal type of the input video data; reading a model database and acquiring a compensation model corresponding to the signal type in the model database; generating compensation coefficients corresponding to the equivalent driving window size according to the compensation model; performing temporal smoothing processing on the compensation coefficients to obtain smoothed compensation coefficients; and performing compensation processing on the current video frame image according to the smoothed compensation coefficients to obtain a compensated video frame image. Compared with the prior art, this application establishes a mapping model between window size and color temperature drift, and a mapping model between window size and peak brightness, and dynamically adjusts the white point compensation coefficient and EOTF / brightness mapping parameters according to the signal type of different mini LED TVs, so that under all typical window sizes, the color accuracy deviation ΔE converges to a range imperceptible to the human eye (ΔE<1.5), achieving window-independent high-consistency color performance.

[0085] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0086] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0087] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0088] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0089] Further reference Figure 8 As a response to the above Figure 2 The implementation of the method shown in this application provides an embodiment of a window-adaptive color accuracy dynamic compensation device, which is similar to... Figure 2 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0090] like Figure 8 As shown, the window-adaptive color accuracy dynamic compensation device 200 of this application embodiment includes: The input video acquisition module 210 is used to acquire input video data; The equivalent driving window size detection module 220 is used to detect the equivalent driving window size of the current video frame image in the input video data in real time. The management mode acquisition module 230 is used to acquire the signal type of the input video data; The compensation model acquisition module 240 is used to read the model database and obtain the compensation model corresponding to the signal type from the model database. The compensation coefficient generation module 250 is used to generate compensation coefficients corresponding to the equivalent driving window size based on the compensation model. The timing smoothing module 260 is used to perform timing smoothing on the compensation coefficients to obtain smoothed compensation coefficients. The compensation processing module 270 is used to perform compensation processing on the current video frame image according to the smoothed compensation coefficient to obtain the compensated video frame image.

[0091] In this embodiment, a window-adaptive color accuracy dynamic compensation device 200 is provided, comprising: an input video acquisition module 210 for acquiring input video data; an equivalent driving window size detection module 220 for real-time detection of the equivalent driving window size of the current video frame image in the input video data; a management mode acquisition module 230 for acquiring the signal type of the input video data; a compensation model acquisition module 240 for reading a model database and acquiring a compensation model corresponding to the signal type from the model database; a compensation coefficient generation module 250 for generating compensation coefficients corresponding to the equivalent driving window size according to the compensation model; a temporal smoothing processing module 260 for performing temporal smoothing processing on the compensation coefficients to obtain smoothed compensation coefficients; and a compensation processing module 270 for performing compensation processing on the current video frame image according to the smoothed compensation coefficients to obtain a compensated video frame image. Compared with existing technologies, this application establishes a mapping model between window size and color temperature drift, and a mapping model between window size and peak brightness. It also dynamically adjusts the white point compensation coefficient and EOTF / brightness mapping parameters according to the signal type of different mini LED TVs. This ensures that the color accuracy deviation ΔE converges to a range imperceptible to the human eye (ΔE<1.5) under all typical window sizes, achieving high consistency color performance independent of the window.

[0092] In some optional implementations of the embodiments of this application, the above-mentioned equivalent driving window size detection module includes: The partition data calculation submodule is used to calculate the number of partitions in the current video frame and the brightness level of each partition; The equivalent driving window size calculation submodule is used to calculate the equivalent driving window size based on the number of partitions and the brightness level of each partition.

[0093] In some optional implementations of the embodiments of this application, when the above signal type is a standard dynamic range mode, the compensation model is a window-color temperature drift mapping model, and the above compensation coefficient generation module includes: The first coordinate offset acquisition submodule is used to obtain the first color coordinate offset corresponding to the equivalent driving window size according to the window-color temperature drift mapping model. The first RGB compensation coefficient calculation submodule is used to calculate the first RGB compensation coefficient based on the first color coordinate offset, and obtain the compensation coefficient.

[0094] In some optional implementations of the embodiments of this application, when the above signal type is a high dynamic range mode, the compensation model is a window-color temperature drift mapping model and a window-peak brightness mapping model, and the above compensation coefficient generation module includes: The second coordinate offset acquisition submodule is used to obtain the second color coordinate offset corresponding to the equivalent driving window size according to the window-color temperature drift mapping model. The second RGB compensation coefficient calculation submodule is used to calculate the second RGB compensation coefficient based on the second color coordinate offset. The first current peak brightness acquisition submodule is used to acquire the first current peak brightness corresponding to the equivalent driving window size according to the window-peak brightness mapping model; The parameter scaling processing submodule is used to obtain the PQ mapping standard parameters and scale the PQ mapping standard parameters according to the first current peak brightness to obtain the PQ mapping compensation coefficient. The first compensation coefficient determination submodule is used to use the second RGB compensation coefficient and the PQ mapping compensation coefficient as compensation coefficients.

[0095] In some optional implementations of the embodiments of this application, when the signal type is Dolby Vision mode, the compensation model is a window-color temperature drift mapping model and a window-peak brightness mapping model, and the generation of the compensation coefficients includes: The third coordinate offset acquisition submodule is used to obtain the third color coordinate offset corresponding to the equivalent driving window size based on the window-color temperature drift mapping model. The third RGB compensation coefficient calculation submodule is used to calculate the third RGB compensation coefficient based on the third color coordinate offset. The second current peak brightness acquisition submodule is used to acquire the second current peak brightness corresponding to the equivalent driving window size according to the window-peak brightness mapping model; The parameter adjustment processing submodule is used to adjust the maximum brightness parameter of Dolby Vision mode according to the second current peak brightness to obtain the current maximum brightness; The brightness mapping curve calculation submodule is used to calculate the brightness mapping curve based on the current maximum brightness and obtain the adaptive brightness mapping compensation coefficient. The second compensation coefficient determination submodule is used to use the third RGB compensation coefficient and the adaptive brightness mapping compensation coefficient as compensation coefficients.

[0096] In some optional implementations of the embodiments of this application, the above-mentioned window-adaptive color accuracy dynamic compensation device 200 further includes: The white dot color coordinate measurement module is used to measure the white dot color coordinates under a preset window size using a spectroradiometer in a dark room environment. The color coordinate offset recording module is used to record the color coordinate offset for each window size based on the white point color coordinates; The first fitting module is used to perform a first fitting process on the preset window size and color coordinate offset based on cubic spline interpolation to obtain the window-color temperature drift mapping model.

[0097] In some optional implementations of the embodiments of this application, the above-mentioned window-adaptive color accuracy dynamic compensation device 200 further includes: The peak brightness measurement module is used to measure the actual peak brightness within a preset window size. The second fitting module is used to perform a second fitting process on the preset window size and the actual peak brightness based on cubic spline interpolation to obtain a window-peak brightness mapping model.

[0098] To address the aforementioned technical problems, embodiments of this application also provide a computer device. Please refer to [link / reference needed]. Figure 9 , Figure 9 This is a basic structural block diagram of a computer device according to an embodiment of this application.

[0099] Computer device 300 includes a memory 310, a processor 320, and a network interface 330 that are interconnected via a system bus. It should be noted that only computer device 300 with components 310-330 is shown in the figure; however, it should be understood that it is not required to implement all the shown components, and more or fewer components can be implemented alternatively. Those skilled in the art will understand that the computer device described here is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0100] Computer devices can include desktop computers, laptops, handheld computers, and cloud servers. These devices allow for human-computer interaction with users through keyboards, mice, remote controls, touchpads, or voice-activated devices.

[0101] The memory 310 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 310 may be an internal storage unit of the computer device 300, such as the hard disk or memory of the computer device 300. In other embodiments, the memory 310 may also be an external storage device of the computer device 300, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. Of course, the memory 310 may include both internal storage units and external storage devices of the computer device 300. In the embodiments of this application, the memory 310 is typically used to store the operating system and various application software installed on the computer device 300, such as computer-readable instructions based on a window-adaptive color accuracy dynamic compensation method. In addition, the memory 310 can also be used to temporarily store various types of data that have been output or will be output.

[0102] In some embodiments, processor 320 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. Processor 320 is typically used to control the overall operation of computer device 300. In embodiments of this application, processor 320 is used to execute computer-readable instructions stored in memory 310 or process data, such as executing computer-readable instructions for a window-adaptive color accuracy dynamic compensation method.

[0103] The network interface 330 may include a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the computer device 300 and other electronic devices.

[0104] The computer device provided in this application establishes a mapping model between window size and color temperature drift, and a mapping model between window size and peak brightness. It dynamically adjusts the white point compensation coefficient and EOTF / brightness mapping parameters according to the signal type of different mini LED TVs, so that the color accuracy deviation ΔE converges to the range imperceptible to the human eye (ΔE<1.5) under all typical window sizes, achieving high consistency color performance independent of the window.

[0105] This application also provides another embodiment, namely, providing a computer-readable storage medium storing computer-readable instructions that can be executed by at least one processor to cause the at least one processor to perform the steps of the window-adaptive color accuracy dynamic compensation method described above.

[0106] The computer-readable storage medium provided in this application establishes a mapping model between window size and color temperature drift, and a mapping model between window size and peak brightness. It dynamically adjusts the white point compensation coefficient and EOTF / brightness mapping parameters according to the signal type of different mini LED TVs, so that the color accuracy deviation ΔE converges to the range imperceptible to the human eye (ΔE<1.5) under all typical window sizes, achieving window-independent high consistency color performance.

[0107] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods of the various embodiments of this application.

[0108] Obviously, the embodiments described above are only some embodiments of this application, not all embodiments. The accompanying drawings show preferred embodiments of this application, but do not limit the patent scope of this application. This application can be implemented in many different forms; rather, the purpose of providing these embodiments is to provide a more thorough and comprehensive understanding of the disclosure of this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments, or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this application's specification and drawings, directly or indirectly applied to other related technical fields, are similarly within the scope of patent protection of this application.

Claims

1. A window-adaptive dynamic color accuracy compensation method, characterized in that, Includes the following steps: Obtain input video data; Real-time detection of the equivalent driving window size of the current video frame image in the input video data; Obtain the signal type of the input video data; Read the model database and obtain the compensation model corresponding to the signal type from the model database; Based on the compensation model, compensation coefficients corresponding to the equivalent driving window size are generated; The compensation coefficients are subjected to time-series smoothing to obtain smoothed compensation coefficients; The current video frame image is compensated according to the smoothed compensation coefficient to obtain the compensated video frame image.

2. The color accuracy dynamic compensation method based on window adaptation according to claim 1, characterized in that, The step of real-time detection of the equivalent driving window size of the current video frame image in the input video data specifically includes the following steps: Calculate the number of partitions and the brightness level of each partition in the current video frame image; The equivalent driving window size is calculated based on the number of partitions and the brightness level of each partition.

3. The color accuracy dynamic compensation method based on window adaptation according to claim 1, characterized in that, When the signal type is a standard dynamic range mode, the compensation model is a window-color temperature drift mapping model. The step of generating compensation coefficients corresponding to the equivalent driving window size based on the compensation model specifically includes the following steps: The first color coordinate offset corresponding to the equivalent driving window size is obtained according to the window-color temperature drift mapping model. The first RGB compensation coefficient is calculated based on the first color coordinate offset to obtain the compensation coefficient.

4. The color accuracy dynamic compensation method based on window adaptation according to claim 1, characterized in that, When the signal type is a high dynamic range mode, the compensation model is a window-color temperature drift mapping model and a window-peak brightness mapping model. The step of generating compensation coefficients corresponding to the equivalent driving window size based on the compensation model specifically includes the following steps: The second color coordinate offset corresponding to the equivalent driving window size is obtained according to the window-color temperature drift mapping model. Calculate the second RGB compensation coefficient based on the second color coordinate offset; The first current peak brightness corresponding to the equivalent driving window size is obtained according to the window-peak brightness mapping model; Obtain the PQ mapping standard parameters, and scale the PQ mapping standard parameters according to the first current peak brightness to obtain the PQ mapping compensation coefficient; The second RGB compensation coefficient and the PQ mapping compensation coefficient are used as the compensation coefficients.

5. The color accuracy dynamic compensation method based on window adaptation according to claim 1, characterized in that, When the signal type is Dolby Vision mode, the compensation model is a window-color temperature drift mapping model and a window-peak brightness mapping model. The step of generating compensation coefficients corresponding to the equivalent driving window size based on the compensation model specifically includes the following steps: The third color coordinate offset corresponding to the equivalent driving window size is obtained according to the window-color temperature drift mapping model. Calculate the third RGB compensation coefficient based on the third color coordinate offset; The second current peak brightness corresponding to the equivalent driving window size is obtained according to the window-peak brightness mapping model; The maximum brightness parameter of the Dolby Vision mode is adjusted based on the second current peak brightness to obtain the current maximum brightness; The brightness mapping curve is calculated based on the current maximum brightness to obtain the adaptive brightness mapping compensation coefficient; The third RGB compensation coefficient and the adaptive brightness mapping compensation coefficient are used as the compensation coefficients.

6. The color accuracy dynamic compensation method based on window adaptation according to claim 3, characterized in that, Before the step of reading the model database, the following steps are also included: In a dark room environment, the color coordinates of the white point under a preset window size are measured using a spectroradiometer. Record the color coordinate offset for each window size based on the white point color coordinates; The window-color temperature drift mapping model is obtained by performing a first fitting process on the preset window size and the color coordinate offset based on cubic spline interpolation.

7. The color accuracy dynamic compensation method based on window adaptation according to claim 4, characterized in that, Before the step of reading the model database, the following steps are also included: Measure the actual peak brightness under the preset window size; The window-peak brightness mapping model is obtained by performing a second fitting process on the preset window size and the actual peak brightness using cubic spline interpolation.

8. A window-adaptive dynamic color accuracy compensation device, characterized in that, include: The input video acquisition module is used to acquire input video data; An equivalent driving window size detection module is used to detect the equivalent driving window size of the current video frame image in the input video data in real time. The management mode acquisition module is used to acquire the signal type of the input video data; The compensation model acquisition module is used to read the model database and acquire the compensation model corresponding to the signal type from the model database. The compensation coefficient generation module is used to generate compensation coefficients corresponding to the equivalent driving window size based on the compensation model. A timing smoothing module is used to perform timing smoothing on the compensation coefficients to obtain smoothed compensation coefficients. The compensation processing module is used to perform compensation processing on the current video frame image according to the smoothed compensation coefficient to obtain the compensated video frame image.

9. A computer device, comprising a memory and a processor, characterized in that, The memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, it implements the steps of the window-adaptive color accuracy dynamic compensation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the window-adaptive color accuracy dynamic compensation method as described in any one of claims 1 to 7.

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