Low-light image enhancement based on the fusion of Bilateral filter MSR and AutoMSRCR

被引：0
|
作者：
Gu W. [1 ]
Ding C. [1 ]
Wei J. [1 ]
Yin Y. [1 ]
Liu X. [1 ]
机构：
[1] College of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming
来源：
Guangxue Jingmi Gongcheng/Optics and Precision Engineering | 2023年 / 31卷 / 24期
关键词：
bilateral filtering; detail enhancement; image enhancement; low light image; weight fusion;
D O I：
10.37188/OPE.20233124.3606
中图分类号：
学科分类号：
摘要：
Aiming at the problem that images taken in low-light environments are affected by the strength of illumination，which leads to poor image quality，this study proposes a low-light image enhancement al⁃ gorithm based on the fusion of bilateral filtering MSR and AutoMSRCR. First，the brightness of the origi⁃ nal low-light image is enhanced using the MSR algorithm based on bilateral filtering in HSV color space. As a result，a brightness-enhanced image with the original color information is obtained. Then，the CLA⁃ HE algorithm is used to enhance the details of the brightness channel based on the Lab color space，and a detail-enhanced image is obtained. Finally，the AutoMSRCR algorithm is used to process the original low-light image and perform weighted fusion with the detail-enhanced image to obtain the final enhanced im⁃ age. Using UCIQE，AG，SD，and IE as evaluation indexes，the proposed algorithm outperformed the MSR，MSRCR，CLAHE，and GAMMA algorithms. The results show that the proposed algorithm opti⁃ mized image quality with UCIQE，AG，SD，and IE reaching values of 0. 472 1，12. 674 2，0. 263 2，and 7. 637 9，respectively. The obtained image contains more color information，is clearer，the image contrast is natural look，and the edge texture information of the image is more complete. That is，images enhanced by this algorithm are of the highest quality. This study provides a feasible method for low-light image en⁃ hancement. © 2023 Chinese Academy of Sciences. All rights reserved.
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页码：3606 / 3617
页数：11
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