Gamma correction system and correction method thereof

Abstract

The invention provides a Gamma correction system and a correction method thereof. The method includes the steps of selecting n gray scale values, calculating n first brightness values corresponding tothe n gray-scale values for each sub-pixel, forming n fitting points by taking the n gray scale values as the horizontal coordinates and the corresponding n first brightness values as the vertical coordinates, fitting the n fitting points to obtain a fitting curve of each sub-pixel, and finally, taking a fitting curve of which the total deviation of the n second brightness values and the n firstbrightness values corresponding to the sub-pixels is smaller than a threshold value as a fitting curve of the sub-pixel and storing the fitting curve into a memory. The brightness corresponding to thegiven gray scale value of each sub-pixel can be obtained according to the fitting curve. The gray scale value does not need to be stored, hardware resources are saved, and only n fitting points needto be fitted in the whole correcting process. The correcting time is greatly shortened.

Description

technical field [0001] The invention relates to the technical field of liquid crystal display, in particular to a Gamma correction system and a correction method thereof. 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 and lookup tables. Manual calibration needs to test the gray value of each gamma gray scale register, compare it with the target gray value, debug the gray value, and cure it. The calibration takes a long time; the looku...

AI Technical Summary

Problems solved by technology

Manual calibration needs to test the gray value of each gamma gray scale register, compare it with the target gray value, debug the gray value, and cure it. The calibration takes a long time; the lookup table needs to store the gray value and the corresponding address in the memory. The input address is checked into the table, and the gray value is output. The correction accuracy is high, but the amount of stored data is large, and it takes up a lot of hardware storage resources.

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