Parallel video image contrast enhancement method and device

Abstract

The present invention relates to a parallel video image contrast enhancement device. The parallel video image contrast enhancement device comprises a scalar processing unit, a local memory, an access control unit, a buffer, a parallel arithmetic logic unit, a state machine and a data interleaving unit. The invention also relates to a parallel video image contrast enhancement method. The method includes the following steps that: step 1, the gray scale histogram of an image to be processed is obtained, and a gray scale mapping lookup table is obtained through calculation; and step 2, based on the gray scale mapping lookup table, gray scale transformation is performed on the image to be processed through a parallel table lookup mode, so that contrast enhancement can be completed. With the parallel video image contrast enhancement method and device of the invention adopted, the contrast of the image can be enhanced, the use efficiency of data can be improved, data interaction between a computing unit and a peripheral memory can be decreased, and the bandwidth pressure of memory access can be reduced.

Description

technical field [0001] The invention belongs to the field of video image processing, in particular to a parallel video image contrast enhancement method and device. Background technique [0002] At present, one of the mainstream development directions of video technology is ultra-high-definition (4K resolution) display technology. Compared with high-definition (1920*1080) video, the number of pixels of 4K video has been increased from 2M to 8M, so higher requirements are placed on the image quality and performance of image enhancement algorithms. [0003] At present, the image contrast enhancement technology is basically based on the histogram equalization algorithm. When performing enhancement, it is necessary to realize the grayscale transformation through a table lookup. When faced with the demand for 4K image processing, it is very likely that the processing capacity is insufficient; at the same time 4K ultra-high-definition images can bring more refined picture effects...

AI Technical Summary

Problems solved by technology

[0003] At present, the image contrast enhancement technology is basically based on the histogram equalization algorithm. When performing enhancement, it is necessary to realize the grayscale transformation through a table lookup. When faced with the demand for 4K image processing, it is very likely that the processing capacity is insufficient; at the same time 4K ultra-high-definition images can bring more refined picture effects, so when the existing contrast enhancement algorithm (mainly the generation algorithm of the mapping curve) is applied to the 4K resolution image, it may be because the algorithm is not accurate enough to control the grayscale mapping curve. without the desired quality

[0004] Therefore, traditional solutions face two difficulties in the ultra-high-definition era. 1. Traditional solutions usually use dedicated hardware circuits with solidified algorithms, making it difficult to flexibly modify the algorithms. When the scheme implements parallel table lookup, it usually uses multiple memory access channels to work in parallel, which increases the hardware cost

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