Gamma correction system and gamma correction method

Abstract

The invention provides a gamma correction system and a gamma correction method. The gamma correction method includes: acquiring the color coordinates and the brightness values of a R sub-pixel, a G sub-pixel, and a B sub-pixel; calculating the target brightness values of the R sub-pixel, the G sub-pixel, and the B sub-pixel according to the color coordinates and the brightness values of the R sub-pixel, the G sub-pixel, and the B sub-pixel, and calculating the brightness value of each sub-pixel at each grayscale according to the brightness value of each of the R sub-pixel, the G sub-pixel, andthe B sub-pixel; determining whether a difference between the brightness value of each sub-pixel of the R sub-pixel, the G sub-pixel, and the B sub-pixel at each grayscale and the target brightness value of each sub-pixel is smaller than a threshold corresponding to the sub-pixel; if so, storing the grayscale value and corresponding brightness value of the sub-pixel. The gamma correction method saves storage resources, greatly shortens correction time and improves correction efficiency.

Description

technical field [0001] The invention relates to the technical field of liquid crystal display, in particular to a Gamma correction system and a Gamma correction method. Background technique [0002] Gamma correction is to edit the Gamma curve of the display screen, and the Gamma curve is the relationship curve between the gray-scale voltage and the corresponding brightness. By adjusting the gray-scale voltage, the brightness of the display screen is edited nonlinearly. At present, the general gamma value standard of the display is 2.2, and the gamma value in the case of image distortion deviates from 2.2, so the gamma correction of the display is essential for accurate display colors. [0003] Traditional gamma correction methods include manual correction, lookup table and multi-point polyline. Manual calibration needs to test the gray value of each gamma gray scale register, compare with the target gray value, adjust the gray value, and cure. The calibration time is long, ...

AI Technical Summary

Problems solved by technology

Manual calibration needs to test the gray value of each gamma gray scale register, compare with the target gray value, adjust the gray value, and cure. The calibration time is long, and the error caused by human and environmental factors is large; The value and the corresponding address are stored in the memory, the input address is checked into the table, and the gray value is output. The calibration accuracy is high, but the amount of stored data is large and takes up a lot of hardware storage resources; multi-point polylines are complicated for gamma values ​​that are not reference points. , large error

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