Laser & Optoelectronics Progress, Volume. 60, Issue 12, 1210022(2023)

Low Illumination Image Enhancement Algorithm Combining Total Variation and Gamma

Shuangshuang Zheng, Wenxue Wei*, and Cong Xu
Author Affiliations
  • School of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, Shandong, China
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    An algorithm for improving low illumination color images that is based on the fusion of full variation and Gamma is proposed to address the issue of low brightness and poor detail. First, the image is divided into illumination and reflection images by using local variation bias and spatial adaptive total variation model (TV), and the weight value is combined with the exponential form of TV to extract better reflection images with texture details. Second, to obtain a better weighted distribution adaptive Gamma correction and an improved brightness corrected image, brightness V is extracted from the original image's HSV space. Finally, weighted fusion of images improved in two different ways yields the final enhancement results. The experimental results demonstrate that the image details processed by the image improvement algorithm are clear, which can effectively address the issue of poor similarity between the enhancement results and the original image brightness structure, and minimize image distortion and artifacts.

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    Shuangshuang Zheng, Wenxue Wei, Cong Xu. Low Illumination Image Enhancement Algorithm Combining Total Variation and Gamma[J]. Laser & Optoelectronics Progress, 2023, 60(12): 1210022

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    Paper Information

    Category: Image Processing

    Received: May. 26, 2022

    Accepted: Jul. 14, 2022

    Published Online: Jun. 5, 2023

    The Author Email: Wei Wenxue (wwxjyh@163.com)

    DOI:10.3788/LOP221707

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