Academic Journal of Computing & Information Science, 2022, 5(4); doi: 10.25236/AJCIS.2022.050412.
Lingfei Chen, Lu Chen
College of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China
To address the problems of local detail loss and sharpness degradation in traditional image enhancement algorithms under low illumination conditions, an image enhancement algorithm based on the Weber-Fechner law is proposed. The adaptive gamma correction function and the adaptive contrast enhancement function are used to reduce the noise interference of the original image, the RGB mode of the original image is converted to HSV mode to improve the overall visual comfort of the image, the classical adaptive correction algorithm is optimised to separate the luminance components into blocks and obtain two images; Finally, the image fusion technique is used to extract the details from the two images and synthesise the final image. The images enhanced are clearer, brighter and more natural than the classical algorithms.
Adaptive image enhancement; low illumination image; Multiscale
Lingfei Chen, Lu Chen. Adaptive Image Enhancement Method Based on Gamma Correction. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 4: 65-70. https://doi.org/10.25236/AJCIS.2022.050412.
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