GPU-Oriented Parallel Algorithm for Histogram Statistical Image Enhancement

Histogram statistics has important applications in the fields of image enhancement and target detection. However, with the increasing size of the image and the higher real-time requirements, the processing process of the histogram statistical local enhancement algorithm is slow and cannot reach the...

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Bibliographic Details
Published in:Jisuanji kexue yu tansuo Vol. 16; no. 10; pp. 2273 - 2285
Main Author: XIAO Han, SUN Lupeng, LI Cailin, ZHOU Qinglei
Format: Journal Article
Language:Chinese
Published: Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press 01.10.2022
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ISSN:1673-9418
Online Access:Get full text
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Summary:Histogram statistics has important applications in the fields of image enhancement and target detection. However, with the increasing size of the image and the higher real-time requirements, the processing process of the histogram statistical local enhancement algorithm is slow and cannot reach the expected satisfactory speed. In view of this deficiency, this paper realizes the parallel processing of histogram statistical image enhancement algorithm on graphics processing unit (GPU) platform, which improves the processing speed of large format digital images. Firstly, the efficiency of data access is improved by making full use of compute unified device architecture (CUDA) active thread block and active thread to process different sub-image blocks and pixels in parallel. Then, the paralle-lization of histogram statistical image enhancement algorithm on GPU platform is realized by using kernel configu-ration parameter optimization and data parallel computing technology. Finally, the efficient data transmission
ISSN:1673-9418
DOI:10.3778/j.issn.1673-9418.2103059