A color correction method and system based on liquid crystal display

Abstract

The present application relates to the technical field of liquid crystal display color correction, and discloses a color correction method and system based on liquid crystal display. The method comprises the following steps: collecting the illumination data of the environment in which the liquid crystal display device is located in real time to obtain environmental light information, and performing abnormality detection on the environmental light information to generate a light abnormality indication signal; when the signal exists, starting color collection of the display panel and the display image, and obtaining panel color measurement values and image color measurement values respectively; fusing the two types of measurement values to perform color accuracy evaluation, and generating a color normal or abnormal signal; and performing color parameter adjustment analysis according to the signal, and outputting target color configuration parameters. The method combines environmental light change triggering correction, performs double-dimension color data collection and fusion evaluation, realizes targeted parameter adjustment, adapts to display requirements under different illuminations, and optimizes the consistency and adaptability of color presentation.

Description

Technical Field

[0001] This invention relates to the field of liquid crystal display color correction technology, specifically to a color correction method and system based on liquid crystal displays. Background Technology

[0002] Liquid crystal displays (LCDs) have become widely used in various fields, including televisions, computer monitors, mobile terminals, and industrial control displays, thanks to their advantages such as thinness, low power consumption, and high resolution. Color, as a core performance indicator of LCDs, directly impacts the user's visual experience. In professional design, audio-visual playback, medical displays, and security monitoring, stringent requirements are placed on the accuracy and consistency of color.

[0003] Currently, color calibration solutions for LCD displays have many limitations. Some solutions only perform a one-time fixed calibration at the factory, with calibration parameters set based on standard laboratory environments, failing to consider the dynamic changes in ambient light during actual use. The intensity and spectral distribution of ambient light change with time and scene, such as fluctuations in indoor natural light, alternation of direct sunlight and shadows outdoors, and the on / off state of artificial light sources. These changes can cause deviations between the displayed colors perceived by users and the standard colors, and fixed calibration parameters cannot adapt to such dynamic changes, resulting in a decrease in display color accuracy.

[0004] Other solutions, while incorporating ambient light acquisition mechanisms, lack effective ambient light anomaly detection mechanisms, merely initiating the color calibration process at fixed time intervals. In this mode, even when ambient light is stable, the calibration process will still be repeatedly executed, resulting in wasted resources; and when sudden lighting anomalies occur, the calibration process may fail to respond in time due to the interval not being reached, causing persistent color deviations and affecting the user experience.

[0005] Existing calibration solutions rely on a limited range of color data acquisition dimensions, mostly collecting only basic color data from the display panel and neglecting the actual color information presented by the displayed image. Panel color data can only reflect the hardware color characteristics of the device itself and cannot reflect the actual display effect of the image content under specific ambient light and panel conditions. This single data source results in an incomplete color evaluation and makes it difficult to accurately capture color deviations in actual display scenarios. Summary of the Invention

[0006] The purpose of this invention is to provide a color correction method and system based on liquid crystal displays to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides a color correction method based on a liquid crystal display, the method comprising:

[0008] The system collects ambient light data of the environment in which the LCD display device is located in real time to obtain ambient light information, and performs anomaly detection on the ambient light information to generate a light anomaly indication signal; when the light anomaly indication signal exists, it starts the display panel color acquisition and the display image color acquisition.

[0009] Obtain panel color measurement values ​​through display panel color acquisition, and obtain image color measurement values ​​through display image color acquisition;

[0010] The color accuracy is evaluated by fusing panel color measurements and image color measurements to generate a normal color signal or an abnormal color signal.

[0011] Based on the normal or abnormal color signal, perform color parameter adjustment analysis and output the target color configuration parameters.

[0012] Preferably, the abnormal detection of ambient light information includes: acquiring ambient light intensity data and chromaticity coordinate data within the current monitoring period; calculating the absolute value of the difference between the ambient light intensity data and the reference ambient light intensity to obtain a light intensity deviation value; simultaneously calculating the Euclidean distance between the chromaticity coordinate data and the standard chromaticity coordinates to obtain a chromaticity deviation value; acquiring the location data and direction data of ambient light sources within the current monitoring period; extracting the light source distance value from the location data; calculating the ratio of the light source distance value to the ideal distance to obtain a distance ratio value; extracting the light source tilt angle value from the direction data; calculating the difference between the light source tilt angle value and the reference tilt angle to obtain a tilt angle difference value; normalizing the light intensity deviation value, chromaticity deviation value, distance ratio value, and tilt angle difference value; assigning weight coefficients to each value and performing a linear combination to obtain a comprehensive ambient light score; comparing the comprehensive ambient light score with a preset threshold; if the comprehensive ambient light score is greater than the threshold, generating a light anomaly indication signal.

[0013] Preferably, the step of acquiring panel color measurement values ​​through display panel color acquisition includes: displaying a test pattern on a liquid crystal display device; capturing the red, green, and blue component values ​​of the test pattern using a color sensor; calculating the percentage error of the red component value relative to the red standard value to obtain the red error rate; calculating the percentage error of the green component value relative to the green standard value to obtain the green error rate; calculating the percentage error of the blue component value relative to the blue standard value to obtain the blue error rate; averaging the red, green, and blue error rates to obtain the channel error mean; simultaneously measuring the brightness level of the test pattern and calculating the relative deviation between the brightness level and the standard brightness to obtain the brightness deviation; and weighted summing the channel error mean and the brightness deviation to obtain the panel color measurement value.

[0014] Preferably, the step of acquiring image color measurement values ​​through image color acquisition includes: acquiring the color histogram of the currently playing image on the liquid crystal display device; extracting saturation distribution values ​​and contrast distribution values ​​from the color histogram; calculating the variance of the saturation distribution values ​​to obtain the saturation fluctuation; calculating the difference between the peak and valley values ​​of the contrast distribution values ​​to obtain the contrast range; simultaneously analyzing the uniformity of the color histogram; calculating the distribution uniformity of color values ​​in each region of the histogram to obtain the color uniformity index; and combining the saturation fluctuation, contrast range, and color uniformity index to calculate a weighted average value to obtain the image color measurement value.

[0015] Preferably, the color accuracy assessment by fusing panel color measurements and image color measurements includes: reading the current ambient light comprehensive score and applying a conversion factor to map the ambient light comprehensive score to environmental influencing factors; performing multi-factor fusion calculation by combining panel color measurements, image color measurements, and environmental influencing factors, wherein the panel color measurements and image color measurements are multiplied by adjustment coefficients and then added to the environmental influencing factors to obtain a color accuracy score; comparing the color accuracy score with a color accuracy baseline, and generating a normal color signal if the color accuracy score is higher than or equal to the baseline, and generating a color abnormal signal if the color accuracy score is lower than the baseline.

[0016] Preferably, the step of performing color parameter adjustment analysis based on normal color signals or abnormal color signals includes: when a normal color signal is generated, a progressive adjustment process is triggered, which includes reading the current brightness setting and contrast setting, calculating the small difference between the brightness setting and the target brightness, and the small difference between the contrast setting and the ideal contrast, and determining the brightness fine-tuning amount and the contrast fine-tuning amount based on the small differences; when an abnormal color signal is generated, a reconstruction adjustment process is triggered, which includes analyzing the red balance value, green balance value and blue balance value of the current color space, calculating the offset of each balance value from the standard color model, and determining the red adjustment value, green adjustment value and blue adjustment value based on the offset.

[0017] Preferably, the specific steps of the progressive adjustment process include: monitoring the real-time brightness output value of the liquid crystal display device, comparing the real-time brightness output value with the preset brightness expectation value to obtain a brightness difference value; monitoring the real-time contrast output value of the liquid crystal display device, comparing the real-time contrast output value with the preset contrast expectation value to obtain a contrast difference value; calculating the brightness adjustment step size proportionally based on the magnitude of the brightness difference value; calculating the contrast adjustment step size proportionally based on the magnitude of the contrast difference value; the brightness adjustment step size and the contrast adjustment step size are the brightness fine-tuning amount and the contrast fine-tuning amount, respectively.

[0018] Preferably, the specific steps of the reconfigurable adjustment process include: displaying a full-screen red test pattern on a liquid crystal display device, measuring the actual output value of the red channel, and calculating the ratio of the actual output value to the red reference value as the red gain coefficient; displaying a full-screen green test pattern, measuring the actual output value of the green channel, and calculating the ratio of the actual output value to the green reference value as the green gain coefficient; displaying a full-screen blue test pattern, measuring the actual output value of the blue channel, and calculating the ratio of the actual output value to the blue reference value as the blue gain coefficient; the red gain coefficient, green gain coefficient, and blue gain coefficient are the red adjustment value, green adjustment value, and blue adjustment value, respectively.

[0019] Preferably, the method further includes, after generating a light anomaly indication signal, classifying the severity of the light anomaly indication signal, and adjusting the start timing of display panel color acquisition and display image color acquisition according to the severity classification result; the severity classification is based on the magnitude of the ambient light comprehensive score, when the ambient light comprehensive score is at a high level, acquisition is started immediately, and when the ambient light comprehensive score is at a low level, acquisition is delayed.

[0020] The specific steps for severity grading include: setting multiple threshold intervals for the comprehensive ambient light score, with each threshold interval corresponding to a severity level; calculating the threshold interval to which the comprehensive ambient light score belongs to determine the severity level; and selecting to execute subsequent data acquisition operations immediately or with a delay based on the severity level, with the delay time dynamically calculated based on the severity level.

[0021] Preferably, the present invention also includes a color correction system based on a liquid crystal display, the system including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, it implements the steps of the color correction method based on a liquid crystal display as described above.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] By acquiring real-time ambient light data of the LCD display device and performing anomaly detection, the system can sensitively capture dynamic changes in ambient light, especially sudden lighting anomalies. Subsequent color acquisition processes are only initiated when a light anomaly indication signal is present. This avoids unnecessary process execution under stable lighting conditions, reduces resource consumption, and ensures that color calibration is initiated promptly when most needed, making the calibration response more targeted.

[0024] This innovative method simultaneously initiates color acquisition from the display panel and color acquisition from the displayed image. These two acquisition processes focus on different dimensions of color information. Panel color measurements reflect the hardware color rendering capabilities of the LCD device, showcasing the panel's basic color characteristics in its current state. Image color measurements directly reflect the color rendering effect of the actual displayed content, aligning with the user's actual visual perception. This dual-dimensional color data acquisition breaks through the limitations of traditional single-source data, enabling more comprehensive and complete acquisition of color-related information, and providing rich foundational data for subsequent color accuracy evaluation.

[0025] In the color accuracy evaluation stage, analysis is performed by fusing panel color measurements and image color measurements, fully integrating information from both hardware characteristics and actual display effects. This fusion analysis mode avoids the one-sidedness of single-data evaluation, and can more comprehensively reflect the actual color presentation status of the LCD display device. This makes the generated normal or abnormal color signals more consistent with actual usage scenarios, significantly improving the reliability of the evaluation results.

[0026] Color parameter adjustment analysis based on color evaluation results enables targeted parameter optimization. When an abnormal color signal is generated, the parameter adjustment analysis can accurately pinpoint the core cause of the color deviation based on dual-dimensional data acquisition and ambient light information, and then output target color configuration parameters adapted to the current scene. When a normal color signal is generated, existing reasonable parameters can be maintained to avoid ineffective adjustments. This dynamic adjustment mode allows color parameters to be deeply adapted to ambient light conditions, device display characteristics, and image content presentation, enabling LCD displays to present a harmonious and consistent color effect under different lighting environments.

[0027] This method requires no complex hardware modifications to LCD display devices. It achieves efficient color correction simply by optimizing data acquisition logic, anomaly detection mechanisms, data fusion methods, and parameter adjustment strategies. It is highly adaptable and can be applied to various LCD display devices, from consumer-grade televisions and mobile phones to professional-grade design monitors and medical displays, all of which can optimize color presentation. Attached Figure Description

[0028] Figure 1 This is a schematic diagram illustrating the working principle of the color correction method based on liquid crystal display described in this invention.

[0029] Figure 2 A flowchart for evaluating color accuracy by fusing measurement values;

[0030] Figure 3 A flowchart for gradual adjustments;

[0031] Figure 4 To gradually adjust the process monitoring chart;

[0032] Figure 5 This diagram illustrates the severity grading and timing of light anomaly indicator signals. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Please see Figure 1 This invention provides a color correction method based on a liquid crystal display (LCD). The method includes: an LCD device equipped with an ambient light sensor and a color sensor; the ambient light sensor continuously collects illumination data around the device, including illumination intensity and chromaticity coordinates, which is transmitted to a processing unit for real-time analysis. The processing unit executes an anomaly detection algorithm on the ambient light information, calculates the light intensity deviation value and chromaticity deviation value, and combines it with the light source position and direction data to generate a comprehensive ambient light score. When the score exceeds a preset threshold, a light anomaly indication signal is generated, triggering the display panel color acquisition and display image color acquisition processes. The display panel color acquisition involves displaying a standard test pattern on the device, using the color sensor to capture the measured values ​​of the red, green, and blue components, calculating the channel error mean and brightness deviation, and obtaining the panel color measurement value. The display image color acquisition analyzes the color histogram of the currently playing image, extracts saturation fluctuation, contrast difference, and color uniformity index, and combines them to form the image color measurement value. The processing unit integrates the panel color measurement value, the image color measurement value, and environmental influencing factors, performing multi-factor fusion calculation to obtain a color accuracy score. The score is compared to a color accuracy baseline. If the score is higher than or equal to the baseline, a normal color signal is generated; otherwise, a color abnormal signal is generated. Depending on the signal type, different color parameter adjustment analyses are performed. For normal color signals, a progressive adjustment process is used to calculate brightness and contrast fine-tuning amounts. For color abnormal signals, a reconstruction adjustment process is used to determine the red, green, and blue adjustment values. The target color configuration parameters are output and applied to the color settings of the LCD display device to achieve dynamic correction.

[0035] Example 1: The processing unit acquires illuminance and chromaticity coordinate data for the current monitoring period from the ambient light sensor. The illuminance data is quantized in lux, while the chromaticity coordinate data is collected based on the CIE 1931 standard chromaticity system. In practice, the processing unit compares the acquired illuminance data with a preset reference illuminance. The reference illuminance is a fixed value pre-stored in the device or a reference value dynamically calculated based on the device's operating environment. The absolute value of the difference between the illuminance data and the reference illuminance is calculated to obtain the illuminance deviation value. This calculation process is completed by the arithmetic operation unit. Simultaneously, the processing unit extracts the x-coordinate and y-coordinate values ​​from the chromaticity coordinate data and calculates the Euclidean distance with the standard chromaticity coordinates. The standard chromaticity coordinates are preset reference points based on the display device's color standard. The Euclidean distance is calculated as the square root of the squared difference, implemented through a dedicated geometric operation module, ultimately outputting the chromaticity deviation value.

[0036] In practical implementation, the ambient light sensor also provides position and orientation data of the light source. The position data includes three-dimensional spatial distance information between the light source and the display device, obtained through triangulation or time-of-flight methods. The processing unit extracts the light source distance value from the position data, i.e., the straight-line distance from the light source to the display panel. The processing unit compares the light source distance value with an ideal distance, which is a recommended value preset for optimal viewing experience. It calculates the ratio of the light source distance value to the ideal distance, obtaining the distance ratio value, which is achieved through division. The orientation data includes the azimuth and pitch angles of the light source relative to the normal of the display panel, measured with the aid of an accelerometer or gyroscope. The processing unit extracts the light source tilt angle value from the orientation data, i.e., the angle between the incident light direction and the normal of the panel. The processing unit compares the light source tilt angle value with a reference tilt angle, which is a preset ideal illumination angle. It calculates the difference between the light source tilt angle value and the reference tilt angle, obtaining the tilt angle difference value. This process is completed by the angle difference calculation module. The processing unit normalizes the light intensity deviation, chromaticity deviation, distance ratio, and tilt angle difference values. The purpose of normalization is to eliminate the influence of different units of measurement, ensuring that all indicators fall within the same numerical range. The normalization process uses a min-max scaling method, performing a linear transformation based on the maximum and minimum values ​​of historically collected data to map each value to a closed interval between 0 and 1. After normalization, the processing unit assigns a corresponding weight coefficient to each normalized value. These weight coefficients are pre-set based on the importance of each factor to color display, with the highest weight coefficient for light intensity deviation, followed by chromaticity deviation, and relatively lower weight coefficients for distance ratio and tilt angle difference. The processing unit then linearly combines the weighted values ​​and performs a weighted summation operation to obtain the overall ambient light score. This weighted summation operation is executed by a linear algebra processor.

[0037] In specific implementation, the processing unit compares the comprehensive ambient light score with a preset threshold. The preset threshold is a dynamically configured critical value based on the device's operating environment and color accuracy requirements, and is stored in non-volatile memory. The comparison operation is implemented using a numerical comparator. If the comprehensive ambient light score is greater than the preset threshold, the current ambient light condition is determined to be abnormal, and the processing unit generates a high-level light anomaly indication signal. If the comprehensive ambient light score is less than or equal to the preset threshold, the light anomaly indication signal remains at a low level. The light anomaly indication signal is a digital signal transmitted to the color acquisition control module through a general-purpose input / output interface to trigger subsequent display panel color acquisition and display image color acquisition processes. In some embodiments, the ambient light data acquisition frequency is configurable. The acquisition frequency is set by modifying the timer interrupt period to adapt to the real-time requirements of different application scenarios. In some embodiments, the historical data range on which the normalization processing relies is updated periodically. The update mechanism uses a sliding window algorithm to retain the sampling data within a certain period of time, ensuring the timeliness of the normalization benchmark.

[0038] It is understandable that the ambient light anomaly detection process is entirely completed within a hardware accelerator or dedicated processing core, with the detection algorithm embedded in read-only memory and sensor data efficiently acquired via direct memory access. It is also understandable that the logic for generating the light anomaly indication signal is implemented using a hardware comparator circuit to ensure low-latency signal response, while eliminating signal jitter through a Schmitt trigger. The ambient light sensor integrates multispectral measurement capabilities, enabling it to simultaneously capture information from multiple bands within the visible light range, providing richer raw data for chromaticity coordinate calculation. Measurements of the light source's position and direction can be combined with image information provided by the camera module, using computer vision algorithms to improve positioning accuracy. This auxiliary data is transmitted to the processing unit via a high-speed serial bus.

[0039] Example 2: Color acquisition of the display panel is achieved through test pattern display on the liquid crystal display device and measurement by a color sensor. The processing unit controls the display controller to sequentially output full-screen monochrome images as test patterns, which are displayed cyclically in the order of red, green, and blue. In specific implementation, the color sensor uses a tristimulus value type sensor or a spectroradiometer. The color sensor is installed at a predetermined position on the display panel and aligned with the display area. The color sensor captures the optical response after each monochrome test pattern has stabilized. The color sensor measures the red component value of the red test pattern, which is the reading of the sensor's red channel; the color sensor measures the green component value of the green test pattern, which is the reading of the sensor's green channel; the color sensor measures the blue component value of the blue test pattern, which is the reading of the sensor's blue channel. The processing unit reads the raw data of the red, green, and blue component values ​​from the color sensor, and the raw data is converted into digital signals by an analog-to-digital converter. The processing unit compares the red component value with a red standard value, which is an ideal red output value pre-stored in non-volatile memory. It calculates the percentage error of the red component value relative to the red standard value to obtain the red error rate, which is equal to the difference between the red component value and the red standard value divided by the red standard value and then multiplied by 100%. The processing unit compares the green component value with a green standard value, which is an ideal green output value pre-stored. It calculates the percentage error of the green component value relative to the green standard value to obtain the green error rate. The processing unit compares the blue component value with a blue standard value, which is an ideal blue output value pre-stored. It calculates the percentage error of the blue component value relative to the blue standard value to obtain the blue error rate. The processing unit takes the arithmetic mean of the red, green, and blue error rates. The calculation process involves adding the three error rates and dividing by three to obtain the channel error mean, which reflects the overall deviation of the color channel.

[0040] In practice, the color sensor measures the brightness level of the test pattern simultaneously with the color components. The brightness level is measured in candela per square meter, and the processing unit reads the brightness level value. The processing unit compares the brightness level with a standard brightness, which is a preset ideal brightness value. It calculates the relative deviation between the brightness level and the standard brightness to obtain the brightness deviation, which is equal to the difference between the brightness level and the standard brightness divided by the standard brightness and then multiplied by 100%. The processing unit performs a weighted summation of the channel error mean and the brightness deviation. The channel error mean is assigned a first weighting coefficient, and the brightness deviation is assigned a second weighting coefficient. The first weighting coefficient is greater than the second weighting coefficient. The result of the weighted summation is used as the panel color measurement value. The panel color measurement value is a dimensionless numerical value used to quantify the color output accuracy of the display panel. In some embodiments, the display duration of the test pattern is a configurable parameter that can be adjusted by modifying the timer settings to ensure that the color sensor has sufficient integration time to obtain a stable reading. In some embodiments, the color sensor performs a self-calibration procedure before each measurement. The self-calibration procedure includes reading the dark current and reference white board values ​​to eliminate the influence of ambient light and sensor drift. The implementation of image color acquisition is independent of the display panel's color acquisition. The processing unit obtains the pixel data of the currently playing image from the display buffer or the graphics processing unit's frame buffer. In specific implementations, the processing unit performs color space conversion on the acquired pixel data, converting the pixel data from the RGB color space to the HSV or Lab color space. This conversion operation is performed by the color management coprocessor. The processing unit generates a color histogram based on the converted color data. The generation of the color histogram includes dividing the color value intervals and counting the number of pixels in each interval. The processing unit extracts saturation distribution values ​​from the color histogram, which are the set of saturation values ​​of all pixels in the image. The processing unit also extracts contrast distribution values ​​from the color histogram, which are the set of brightness variations in local areas of the image.

[0041] The processing unit calculates the variance of the saturation distribution values. The variance calculation uses standard statistical methods: first, the average saturation value is calculated; then, the sum of the squared differences between each saturation value and the average is calculated; finally, this is divided by the total number of saturation values ​​to obtain the saturation fluctuation. The processing unit analyzes the contrast distribution values, identifies the maximum and minimum values, and calculates the difference between the maximum and minimum values ​​to obtain the contrast range. The processing unit analyzes the uniformity of the color histogram, dividing the color histogram into multiple continuous intervals, calculating the frequency of pixels in each interval, and applying the information entropy formula or uniformity measurement formula to calculate the distribution uniformity, obtaining the color uniformity index. The processing unit combines the saturation fluctuation, contrast range, and color uniformity index, normalizes each value, assigns a third, fourth, and fifth weighting coefficient, and takes a weighted average to obtain the image color measurement value. It can be understood that the color histogram analysis uses a streaming processing approach; the processing unit scans pixel data line by line and updates the histogram statistics, avoiding the storage of complete image frames to reduce memory usage. It is understandable that the calculations of saturation fluctuation, contrast difference, and color uniformity index can be performed in parallel, with processing speed improved through single instruction multiple data instruction set or hardware accelerators.

[0042] Optionally, the generation of the color histogram can consider the spatial information of the image by dividing the image into multiple regions and generating an independent histogram for each region, then merging the regional histograms to obtain the global color histogram. Optionally, the processing unit can preprocess the image data before generating the color histogram. Preprocessing operations include downsampling, color quantization, or filtering to reduce computational complexity. The calculation cycle of the image color measurement values ​​is synchronized with the video frame rate to ensure real-time performance. The display image color acquisition process shares some computational resources with the display panel color acquisition process, but has independent control logic and data paths.

[0043] Example 3: See Figure 2 The implementation of color accuracy assessment by fusing panel color measurements and image color measurements involves a multi-factor calculation process. The processing unit reads the current ambient light comprehensive score from memory, which is the output of the ambient light anomaly detection module. In specific implementation, the processing unit applies a conversion factor to map the ambient light comprehensive score to environmental influencing factors. The conversion factor is a pre-determined scaling coefficient stored in the device's configuration register. The mapping operation is achieved through multiplication. The formula for calculating the environmental influencing factors is:

[0044]

[0045] in: Representing environmental impact factors, Represents the conversion factor. This represents the overall environmental light score. Environmental influencing factors. Environmental factors characterize the degree of interference caused by ambient lighting conditions on color perception. The numerical value ranges from 0 to 1. The processing unit combines panel color measurements, image color measurements, and environmental influencing factors. Multi-factor fusion calculations are performed. Panel color measurement values ​​are obtained from the display panel color acquisition module, and image color measurement values ​​are obtained from the display image color acquisition module.

[0046] In practical implementation, the multi-factor fusion calculation first multiplies the panel color measurement value and the image color measurement value by adjustment coefficients. The adjustment coefficient for the panel color measurement value is called the first adjustment coefficient, and the adjustment coefficient for the image color measurement value is called the second adjustment coefficient. The first and second adjustment coefficients are pre-set based on the characteristics of the display device and the application scenario, and are stored in non-volatile memory. The calculation of multiplying the panel color measurement value by the first adjustment coefficient is performed by the arithmetic logic unit, while the calculation of multiplying the image color measurement value by the second adjustment coefficient is performed in parallel. The processing unit then combines the weighted panel color measurement value and the weighted image color measurement value with environmental influencing factors. The addition and summation operations generate a color accuracy score, which is a comprehensive quantitative indicator. This color accuracy score is then compared to a color accuracy baseline, a threshold dynamically set based on color quality standards. The comparison is implemented using a numerical comparator circuit.

[0047] In specific implementation, if the color accuracy score is higher than or equal to the color accuracy baseline, the processing unit generates a normal color signal, which is a high-level digital signal. If the color accuracy score is lower than the color accuracy baseline, the processing unit generates a color abnormality signal, which is a low-level digital signal. The normal color signal and the color abnormality signal are transmitted to the color parameter adjustment and analysis module via the system bus. In some embodiments, the color accuracy baseline can be adaptively adjusted according to the type of displayed content; for example, a more lenient baseline is used when browsing text, and a more stringent baseline is used when viewing images. In some embodiments, the conversion factor... The value can be calibrated according to the model and accuracy of the ambient light sensor. The calibration process is performed before the device leaves the factory or during regular maintenance. In some embodiments, the ratio of the first adjustment coefficient and the second adjustment coefficient remains constant, but the absolute value may be fine-tuned as the device ages or temperature changes. The fine-tuning process is completed through a feedback mechanism based on historical calibration data.

[0048] When a color normality signal is generated, the processing unit triggers a progressive adjustment process. This process includes reading the current brightness and contrast settings, which are retrieved from the display driver's registers. The processing unit calculates the minute difference between the current brightness setting and the target brightness, which is an ideal value dynamically calculated based on ambient light intensity and user preferences. The processing unit also calculates the minute difference between the current contrast setting and the ideal contrast, which is a preset reference value based on content type and display standards. Based on the magnitude of these minute differences, the processing unit determines the brightness and contrast fine-tuning amounts, which are adjustment step sizes. When a color abnormality signal is generated, the processing unit triggers a reconstructive adjustment process. This process includes analyzing the red, green, and blue balance values ​​of the current color space, which are read from the color management system's configuration file.

[0049] In practical implementation, the processing unit calculates the offset of the red balance value from the red component in the standard color model, the offset of the green balance value from the green component in the standard color model, and the offset of the blue balance value from the blue component in the standard color model. The offset is calculated using a percentage difference method, i.e., the difference between the balance value and the standard value divided by the standard value. Based on the magnitude and direction of the offset, the processing unit determines the red, green, and blue adjustment values, which are correction values ​​used to directly modify the color gain parameters. It can be understood that the multi-factor fusion calculation process can be efficiently implemented using a hardware multiplier-accumulator, which can complete multiplication and addition operations within one clock cycle. It can also be understood that the dynamic adjustment mechanism of the color accuracy baseline relies on the output of the content analysis module, which identifies the type and color characteristics of the currently displayed content in real time.

[0050] Optionally, environmental impact factors The calculation can take into account changes in ambient light color temperature, and the conversion factor can be corrected by introducing a color temperature compensation factor. The color temperature compensation factor is calculated based on the ambient light spectral distribution. The generation logic for normal and abnormal color signals includes a dejitter mechanism. This mechanism requires the signal state to remain unchanged for multiple consecutive calculation cycles before output is confirmed, preventing false triggering due to instantaneous fluctuations. The progressive adjustment process and the refactoring adjustment process share some computing resources but have independent control state machines to ensure that the two processes are not activated simultaneously. After completing the color accuracy evaluation, the processing unit writes the normal or abnormal color signal along with the color accuracy score into the shared memory area for the color parameter adjustment and analysis module to read. The color parameter adjustment and analysis module selects and executes the corresponding adjustment process based on the signal type and applies the finally determined target color configuration parameters to the display device.

[0051] Example 4: See Figure 3 The progressive adjustment process includes continuous monitoring and parameter calculation of the output status of the LCD device. The processing unit reads the real-time brightness output value from the embedded brightness sensor or from the display driver, and the real-time brightness output value is quantified in nits. In practice, the processing unit compares the real-time brightness output value with a preset brightness expectation value. The preset brightness expectation value is an ideal value dynamically generated based on ambient light intensity, user settings, and content type through a lookup table method or calculation model. The arithmetic difference between the real-time brightness output value and the preset brightness expectation value is calculated and its absolute value is taken to obtain the brightness difference value. Simultaneously, the processing unit calculates the real-time contrast output value through the image processing coprocessor or directly from the display buffer data. The real-time contrast output value is defined as the ratio of the maximum brightness to the minimum brightness in the image frame. The processing unit compares the real-time contrast output value with a preset contrast expectation value, which is a reference value set according to display standards and human visual characteristics. The arithmetic difference between the real-time contrast output value and the preset contrast expectation value is calculated and its absolute value is taken to obtain the contrast difference value. The processing unit calculates the brightness adjustment step size proportionally based on the magnitude of the brightness difference value. This proportional calculation uses a linear interpolation method; the larger the brightness difference value, the larger the brightness adjustment step size, and vice versa. The calculation of the brightness adjustment step size is based on a predefined mapping relationship. Similarly, the processing unit calculates the contrast adjustment step size proportionally based on the magnitude of the contrast difference value. A direct proportional relationship also exists between the contrast difference value and the contrast adjustment step size. The brightness adjustment step size and contrast adjustment step size are the final output brightness and contrast fine-tuning values, which are signed integer values, with the sign representing the adjustment direction. These values ​​are encapsulated into data packets and sent to the display control module via an internal communication bus. In practice, the monitoring of brightness and contrast difference values ​​is performed cyclically at fixed time intervals. The length of these time intervals can be configured through system registers to ensure the real-time nature and smoothness of the adjustments. The preset brightness expectation value and preset contrast expectation value can have different values ​​based on different display modes (such as standard mode, cinema mode, reading mode). The processing unit loads the corresponding expectation value from the preset configuration file according to the currently active display mode.

[0052] The specific steps of the reconfigurable adjustment process involve sequentially displaying full-screen monochrome test patterns on an LCD display device and performing color channel measurements. The processing unit controls the graphics generator to sequentially output full-screen red, green, and blue test patterns. In practice, a high-precision color analyzer or spectrophotometer is used to measure the optical output of each monochrome test pattern. The color analyzer is mounted directly in front of the display panel and is rigorously calibrated. When displaying the full-screen red test pattern, the color analyzer measures the actual output value of the red channel, which is the radiance value measured by the instrument within the red wavelength range. The processing unit reads the actual output value of the red channel from the color analyzer and compares it with a red reference value. The red reference value is the ideal red output value determined according to the target color standard (such as sRGB or DCI-P3). The ratio of the actual output value of the red channel to the red reference value is calculated, and this ratio is used as the red gain coefficient. When displaying the full-screen green test pattern, the color analyzer measures the actual output value of the green channel, and the processing unit calculates the ratio of the actual output value of the green channel to the green reference value to obtain the green gain coefficient. When displaying a full-screen blue test pattern, the color analyzer measures the actual output value of the blue channel. The processing unit calculates the ratio of the actual output value of the blue channel to the blue reference value, obtaining the blue gain coefficient. The red, green, and blue gain coefficients are the final red, green, and blue adjustment values ​​that need to be output. These red, green, and blue adjustment values ​​are floating-point numbers directly used to configure the color gain lookup table of the display engine. It is understood that the display duration of the full-screen monochrome test pattern must be long enough to ensure that the color analyzer completes a full measurement cycle; the display duration is precisely controlled by a hardware timer. Before each measurement, the color analyzer may perform an automatic zeroing and calibration sequence to eliminate the influence of ambient light and instrument drift on the measurement results.

[0053] Optionally, the red, green, and blue reference values ​​may not be fixed values, but rather dynamically calculated based on the target white point of the display panel. For example, when the target color temperature is D65, the red, green, and blue reference values ​​need to satisfy the tristimulus value ratio. Optionally, the gain coefficient calculation can consider the nonlinear gamma characteristics of the display panel. By converting the actual output value and reference value to a linear light space before performing the ratio calculation, a more accurate adjustment effect can be obtained. The reconfigurable adjustment process typically runs in calibration mode, which temporarily interrupts normal content display when calibration mode is activated. The progressive adjustment process runs continuously in the background and is transparent to the user. The parameters generated by the two adjustment processes—brightness fine-tuning, contrast fine-tuning, red adjustment value, green adjustment value, and blue adjustment value—are ultimately summarized into target color configuration parameters and written into the corresponding registers of the display hardware. Refer to Table 1 for the mapping relationship between the brightness adjustment step size and contrast adjustment step size and the difference value. The numerical relationships in the table are stored in the device's non-volatile memory. The processing unit determines the precise adjustment step size by looking up the table and combining it with linear interpolation.

[0054] Table 1: Brightness and Contrast Adjustment Step Size Mapping Table

[0055]

[0056] When calculating the brightness adjustment step size, the processing unit first normalizes the brightness difference values ​​to the range of [0.0, 1.0], and then queries the brightness and contrast adjustment step size mapping table to find the corresponding brightness adjustment step size. The process for determining the contrast adjustment step size is similar. The range of difference values ​​in the brightness and contrast adjustment step size mapping table is divided based on historical adjustment data and a visual perception model to ensure that the adjustment process is both smooth and effective. In some embodiments, the contents of the brightness and contrast adjustment step size mapping table can be dynamically updated according to the panel aging degree or ambient temperature, and the adaptive mechanism is implemented by monitoring long-term parameter drift.

[0057] See Figure 4 This document presents complete monitoring data for the progressive adjustment process of an LCD display device. The charts include curves showing the changes in brightness and contrast differences over time, reflecting the deviation between the display device's output state and the desired value. The charts also display the brightness and contrast adjustment step sizes calculated based on the difference values; these step sizes are dynamically adjusted based on a preset mapping relationship. The brightness difference curve in the chart shows the normalized difference between the device's real-time brightness output and the preset desired value, while the contrast difference curve reflects the deviation between the real-time contrast output and the target contrast. The adjustment step size curve shows the fine-tuning amount automatically calculated by the system based on the magnitude of the difference value; a larger difference value results in a larger adjustment step size, while a smaller difference value uses a smaller adjustment step size, ensuring the smoothness and real-time performance of the adjustment process.

[0058] Example 5: Severity Grading of Light Anomaly Indication Signals Based on Ambient Light Comprehensive Score Analysis. The processing unit initiates a grading process immediately upon generating a light anomaly indication signal. In this implementation, the processing unit sets multiple threshold intervals for the ambient light comprehensive score. These intervals are divided based on the statistical distribution of a large amount of experimental data, for example, three threshold intervals: [0.0, 0.4), [0.4, 0.7), and [0.7, 1.0]. Each threshold interval corresponds to a severity level: [0.0, 0.4) corresponds to severity level one, [0.4, 0.7) to severity level two, and [0.7, 1.0] to severity level three. The processing unit calculates the threshold interval to which the current ambient light comprehensive score belongs by sequentially comparing the ambient light comprehensive score with the upper and lower boundaries of each interval. For example, when the ambient light comprehensive score is 0.85, it is greater than or equal to 0.7 and less than or equal to 1.0; therefore, the ambient light comprehensive score belongs to the [0.7, 1.0] interval, corresponding to severity level three.

[0059] The processing unit selects the start time for display panel color acquisition and display image color acquisition based on the severity level. When the ambient light comprehensive score is at severity level three, the processing unit immediately sends a start command to the color acquisition control module, triggering the synchronous execution of the display panel color acquisition and display image color acquisition processes. When the ambient light comprehensive score is at severity level one or two, the processing unit delays sending the start command, with the delay time dynamically calculated based on the severity level. Severity level one corresponds to a longer delay time, and severity level two corresponds to a shorter delay time. The delay time is calculated using a linear function, where the delay time equals the base delay time multiplied by a severity level coefficient. The coefficient for severity level one is 3.0, and the coefficient for severity level two is 1.5. The base delay time is set to 2 seconds. For example, for severity level one, the delay time equals 2 seconds multiplied by 3.0, resulting in 6 seconds; for severity level two, the delay time equals 2 seconds multiplied by 1.5, resulting in 3 seconds. After determining the delay time, the processing unit starts a hardware timer, and subsequent acquisition operations are only executed after the timer expires.

[0060] In practical implementation, the number and range of threshold intervals can be configured according to device type and usage scenario. For example, five threshold intervals may be set in high-end professional monitors to achieve more refined grading. The boundary values ​​of the threshold intervals are stored in erasable programmable read-only memory, allowing modification via software updates. The mapping relationship between severity level and latency can also be adjusted through a configuration table containing a severity level index and the corresponding latency coefficient. The processing unit continuously monitors changes in the ambient light comprehensive score during the latency period. If the ambient light comprehensive score changes during the latency period and causes the severity level to increase, the processing unit may interrupt the current latency and immediately start the acquisition process. In some embodiments, severity level three not only triggers immediate acquisition but may also simultaneously trigger a system alarm or user prompt, notifying the user of the current severe ambient light conditions. In some embodiments, the calculation of latency can take into account the device's current battery status, automatically extending the latency in low-battery mode to save energy.

[0061] Optionally, severity grading can consider the changing trend of the ambient light comprehensive score. For example, the processing unit records the ambient light comprehensive score for the most recent monitoring periods and calculates the rate of change. If the ambient light comprehensive score is rising rapidly, even if the current score belongs to severity level two, the acquisition process may be triggered prematurely. Optionally, the definition of severity level can be more refined. For example, severity level three can be further divided into 3A and 3B levels. Level 3A corresponds to the score range [0.7, 0.85], and level 3B corresponds to the score range [0.85, 1.0]. Level 3B may trigger a more urgent processing procedure. Optionally, for certain abnormal ambient light patterns, such as flickering or severe fluctuations, the processing unit can override the grading result and directly perform immediate acquisition, regardless of which range the ambient light comprehensive score is in. It can be understood that the entire logic of severity grading is implemented by a dedicated state machine. The state machine transitions between different states according to the input value of the ambient light comprehensive score, and each state corresponds to a delay time and action.

[0062] In a specific example, suppose the ambient light sensor detects that the indoor lights suddenly turn off, leaving only the afterglow of the setting sun outside the window, and the overall ambient light score is calculated to be 0.25. The processing unit compares the overall ambient light score of 0.25 with a preset threshold range. 0.25 falls within the range [0.0, 0.4), corresponding to severity level one. Based on severity level one, the processing unit queries the delay coefficient, which is 3.0. Combining this with the base delay time of 2 seconds, the processing unit calculates a delay time of 6 seconds. The processing unit starts a 6-second countdown timer. During the 6-second delay, the processing unit continues to periodically calculate the overall ambient light score. Suppose that in the 4th second of the delay, the user turns on the main indoor light, and the overall ambient light score quickly changes to 0.68. The processing unit detects the change in the overall ambient light score and recalculates the severity level. 0.68 falls within the range [0.4, 0.7), corresponding to severity level two. The processing unit immediately cancels the original 6-second delay timer and calculates a new delay time of 3 seconds (2 seconds multiplied by 1.5) based on severity level 2. However, since 4 seconds of the original delay have already elapsed, the new delay time of 3 seconds is less than the elapsed time. Therefore, the processing unit does not wait and immediately triggers the display panel color acquisition and display image color acquisition process. This example illustrates how the severity grading mechanism dynamically responds to environmental changes to ensure that the acquisition operation is performed at the optimal time.

[0063] In another specific example, the ambient light sensor detected direct midday sunlight on the display screen, and the overall ambient light score remained consistently high at 0.92. The processing unit determined that the overall ambient light score of 0.92 fell within the [0.7, 1.0] range, corresponding to severity level three. According to the processing rules for severity level three, the processing unit immediately generated a start command, triggering color acquisition from the display panel and the displayed image without any delay. Simultaneously, the processing unit may send a notification to the user interface, suggesting adjusting the monitor position or enabling high brightness mode. During the acquisition process, the processing unit continued to monitor the overall ambient light score. If the score dropped to 0.60 due to cloud cover or other reasons, the processing unit recorded this change but did not interrupt the already initiated acquisition process, ensuring the integrity of the current calibration process. After acquisition, the processing unit used the latest overall ambient light score of 0.60 to evaluate color accuracy. This score falls under severity level two, but the evaluation process is based on the environmental conditions at the time of acquisition, reflecting the system's real-time performance.

[0064] See Figure 5This chart illustrates the severity grading mechanism for abnormal ambient light conditions and the corresponding acquisition triggering strategy. The chart clearly delineates three severity levels using different colored background areas, and the overall ambient light score curve reflects the dynamic changes in ambient light conditions. The chart marks immediate acquisition trigger points and delayed acquisition points, demonstrating the system's strategy of intelligently determining acquisition timing based on severity level. When the overall ambient light score enters the high-level range, the system immediately triggers the color acquisition process; when the score is in the low to medium level, the system calculates the corresponding delay time based on severity, continuing to monitor environmental changes during the delay period. This grading mechanism ensures that color acquisition operations are performed at the optimal time, avoiding unnecessary frequent acquisitions and enabling timely correction when ambient light conditions are poor. The chart also demonstrates the system's dynamic response capability; when ambient light conditions change during the delay period, the system can reassess the severity level and adjust the acquisition strategy.

[0065] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A color correction method based on liquid crystal display, characterized in that, The method includes: The system collects ambient light data of the environment in which the LCD display device is located in real time to obtain ambient light information, and performs anomaly detection on the ambient light information to generate a light anomaly indication signal; when the light anomaly indication signal exists, it starts the display panel color acquisition and the display image color acquisition. Obtain panel color measurement values ​​through display panel color acquisition, and obtain image color measurement values ​​through display image color acquisition; The color accuracy is evaluated by fusing panel color measurements and image color measurements to generate a normal color signal or an abnormal color signal. Based on the normal or abnormal color signal, perform color parameter adjustment analysis and output the target color configuration parameters.

2. The color correction method based on liquid crystal display according to claim 1, characterized in that, The anomaly detection of ambient light information includes: acquiring ambient light intensity data and chromaticity coordinate data within the current monitoring period; calculating the absolute value of the difference between the ambient light intensity data and the reference ambient light intensity to obtain the light intensity deviation value; simultaneously calculating the Euclidean distance between the chromaticity coordinate data and the standard chromaticity coordinates to obtain the chromaticity deviation value; acquiring the location data and direction data of ambient light sources within the current monitoring period; extracting the light source distance value from the location data; calculating the ratio of the light source distance value to the ideal distance to obtain the distance ratio value; extracting the light source tilt angle value from the direction data; calculating the difference between the light source tilt angle value and the reference tilt angle to obtain the tilt angle difference value; normalizing the light intensity deviation value, chromaticity deviation value, distance ratio value, and tilt angle difference value; assigning weight coefficients to each value and performing a linear combination to obtain a comprehensive ambient light score; comparing the comprehensive ambient light score with a preset threshold; if the comprehensive ambient light score is greater than the threshold, a light anomaly indication signal is generated.

3. The color correction method based on liquid crystal display according to claim 2, characterized in that, The process of acquiring panel color measurement values ​​through display panel color acquisition includes: displaying a test pattern on a liquid crystal display device; capturing the red, green, and blue component values ​​of the test pattern using a color sensor; calculating the percentage error of the red component value relative to the red standard value to obtain the red error rate; calculating the percentage error of the green component value relative to the green standard value to obtain the green error rate; calculating the percentage error of the blue component value relative to the blue standard value to obtain the blue error rate; averaging the red, green, and blue error rates to obtain the channel error mean; simultaneously measuring the brightness level of the test pattern and calculating the relative deviation between the brightness level and the standard brightness to obtain the brightness deviation; and weighted summing the channel error mean and the brightness deviation to obtain the panel color measurement value.

4. The color correction method based on liquid crystal display according to claim 3, characterized in that, The process of acquiring image color measurement values ​​through image color acquisition includes: acquiring the color histogram of the currently playing image on the liquid crystal display device; extracting saturation distribution values ​​and contrast distribution values ​​from the color histogram; calculating the variance of the saturation distribution values ​​to obtain the saturation fluctuation; calculating the difference between the peak and valley values ​​of the contrast distribution values ​​to obtain the contrast range; simultaneously analyzing the uniformity of the color histogram; calculating the uniformity of color value distribution in each region of the histogram to obtain the color uniformity index; and combining the saturation fluctuation, contrast range, and color uniformity index to calculate a weighted average value to obtain the image color measurement value.

5. The color correction method based on liquid crystal display according to claim 4, characterized in that, The color accuracy assessment by fusing panel color measurements and image color measurements includes: reading the current ambient light comprehensive score and applying a conversion factor to map the ambient light comprehensive score to environmental influencing factors; combining panel color measurements, image color measurements, and environmental influencing factors to perform multi-factor fusion calculation, wherein the panel color measurements and image color measurements are multiplied by adjustment coefficients and then added to the environmental influencing factors to obtain a color accuracy score; comparing the color accuracy score with a color accuracy baseline, if the color accuracy score is higher than or equal to the baseline, a normal color signal is generated; if the color accuracy score is lower than the baseline, an abnormal color signal is generated.

6. The color correction method based on liquid crystal display according to claim 5, characterized in that, The analysis of color parameter adjustment based on normal or abnormal color signals includes: when a normal color signal is generated, a progressive adjustment process is triggered, which includes reading the current brightness and contrast settings, calculating the small difference between the brightness setting and the target brightness, and the small difference between the contrast setting and the ideal contrast, and determining the brightness and contrast fine-tuning amounts based on the small differences; when an abnormal color signal is generated, a reconstructive adjustment process is triggered, which includes analyzing the red, green, and blue balance values ​​of the current color space, calculating the offset of each balance value from the standard color model, and determining the red, green, and blue adjustment values ​​based on the offsets.

7. A color correction method based on a liquid crystal display according to claim 6, characterized in that, The specific steps of the progressive adjustment process include: monitoring the real-time brightness output value of the liquid crystal display device, comparing the real-time brightness output value with the preset expected brightness value to obtain the brightness difference value; monitoring the real-time contrast output value of the liquid crystal display device, comparing the real-time contrast output value with the preset expected contrast value to obtain the contrast difference value; calculating the brightness adjustment step size proportionally based on the magnitude of the brightness difference value; calculating the contrast adjustment step size proportionally based on the magnitude of the contrast difference value; the brightness adjustment step size and the contrast adjustment step size are the brightness fine-tuning amount and the contrast fine-tuning amount, respectively.

8. The color correction method based on liquid crystal display according to claim 7, characterized in that, The specific steps of the reconfigurable adjustment process include: displaying a full-screen red test chart on a liquid crystal display device, measuring the actual output value of the red channel, and calculating the ratio of the actual output value to the red reference value as the red gain coefficient; displaying a full-screen green test chart, measuring the actual output value of the green channel, and calculating the ratio of the actual output value to the green reference value as the green gain coefficient; displaying a full-screen blue test chart, measuring the actual output value of the blue channel, and calculating the ratio of the actual output value to the blue reference value as the blue gain coefficient; the red gain coefficient, green gain coefficient, and blue gain coefficient are the red adjustment value, green adjustment value, and blue adjustment value, respectively.

9. A color correction method based on a liquid crystal display according to claim 8, characterized in that, The method further includes, after generating a light anomaly indication signal, classifying the severity of the light anomaly indication signal, and adjusting the start timing of display panel color acquisition and display image color acquisition according to the severity classification result; the severity classification is based on the magnitude of the ambient light comprehensive score, when the ambient light comprehensive score is high, acquisition is started immediately, when the ambient light comprehensive score is low, acquisition is delayed. The specific steps for severity grading include: setting multiple threshold intervals for the comprehensive ambient light score, with each threshold interval corresponding to a severity level; calculating the threshold interval to which the comprehensive ambient light score belongs to determine the severity level; and selecting to execute subsequent data acquisition operations immediately or with a delay based on the severity level, with the delay time dynamically calculated based on the severity level.

10. A color correction system based on a liquid crystal display, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the color correction method based on liquid crystal display as described in any one of claims 1 to 9.

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