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Volume 45 Issue 2
Feb.  2023
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YOU Dazhang, TAO Jiatao, ZHANG Yepeng, ZHANG Min. Low-light Image Enhancement Based on Gray Scale Transformation and Improved Retinex[J]. Infrared Technology , 2023, 45(2): 161-170.
Citation: YOU Dazhang, TAO Jiatao, ZHANG Yepeng, ZHANG Min. Low-light Image Enhancement Based on Gray Scale Transformation and Improved Retinex[J]. Infrared Technology , 2023, 45(2): 161-170.
shu

Low-light Image Enhancement Based on Gray Scale Transformation and Improved Retinex

  • 1.

    School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China

  • 2.

    Hubei Key Lab of Manufacture Quality Engineering, Wuhan 430068, China

  • 3.

    Engineering and Technology College, Hubei University of Technology, Wuhan 430068, China

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  • Received Date: May 13, 2022
  • Revised Date: August 21, 2022
    Graphical Abstract
    • Abstract
  • Aiming at the problems of low contrast and blurred details of images captured under low-light conditions due to the influence of light and the environment, important information is lost, and an image enhancement method based on grayscale transformation and improved Retinex is proposed. First, the global grayscale transformation function optimized by the gravity search algorithm(GSA) is used to perform grayscale transformation on the grayscale image of each RGB channel of the image to enhance the image illumination intensity and make it closer to the uniform illumination scene. The image is then converted to the HSV color space. The V channel (luminance channel) is processed by the improved multi-scale Retinex (MSR) algorithm; range-based adaptive bilateral filtering and Gabor filtering are used as the surround function of the Retinex algorithm, and the characteristics of the two filters are combined to enhance the brightness and detail of the image. Finally, gamma correction is used to avoid image color casts caused by image fusion. The experimental results show that the enhanced image processed by this method is better than that processed by other methods in subjective and objective evaluation, the color distortion of the image is smaller, and the details are clearer, which paves the way for the subsequent application of the image.
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    • References (20)
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