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  • Received: Dec. 10, 2019

    Accepted: Feb. 25, 2020

    Posted: Oct. 1, 2020

    Published Online: Oct. 17, 2020

    The Author Email: Zhang Hongying (carole_zhang0716@163.com)

    DOI: 10.3788/LOP57.201504

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    Hongying Zhang, Jindong Zhao. RetinexNet Low Illumination Image Enhancement Algorithm in HSV Space[J]. Laser & Optoelectronics Progress, 2020, 57(20): 201504

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Laser & Optoelectronics Progress, Vol. 57, Issue 20, 201504 (2020)

RetinexNet Low Illumination Image Enhancement Algorithm in HSV Space

Zhang Hongying* and Zhao Jindong

Author Affiliations

  • College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China

Abstract

Aim

ing at the problem of color distortion and edge blur in RetinexNet low illumination image enhancement algorithm, we propose an improved RetinexNet algorithm. First, using the relatively independent characteristics of each channel in the HSV (Hue, Saturation, Value) color space model to enhance the brightness component. Then, the correlation coefficient is used to adaptively adjust the saturation component with the change of the brightness component to avoid changes in image color perception. Finally, aiming at the edge blur problem of the enhanced image, Laplace algorithm is adopted to sharpen the reflectivity image to enhance the ability of detail expression of the image. Experimental results show that the proposed algorithm could effectively enhance the details of the image, keep the overall color of the image consistent with the original image, and improve the visual effect of the image.

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