Retinex-SIE: self-supervised low-light image enhancement method based on Retinex and homomorphic filtering transformation

Jiachang Yang; Qin Cheng; Jianming Liu

doi:10.1117/12.2671157

28 April 2023 Retinex-SIE: self-supervised low-light image enhancement method based on Retinex and homomorphic filtering transformation

Jiachang Yang, Qin Cheng, Jianming Liu

Author Affiliations +

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126101J (2023) https://doi.org/10.1117/12.2671157
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Low-light images suffer from low visibility, much noise, uneven illumination distribution, etc. Many existing methods have problems such as over enhancement or insufficient detail enhancement when dealing with low-light images with uneven illumination distribution. To remedy the above shortcomings, we propose a Retinex-based self-supervised low-light image enhancement model (Retinex-SIE), which is mainly composed of three parts: Retinex-based self-supervised image decomposition network (Retinex-DNet), nonlinear conditional illumination enhancement function (NCIEF), and Image Reconstruction (IR). First, a uniform illumination image of the same scene with the low-light image is generated by homomorphic filtering transformation, and the low-light image and the uniform illumination image are input into Retinex-DNet for decomposition to obtain reflectivity, noise and illumination. Then, NCIEF is used to enhance the illumination after decomposition. Finally, the final enhanced image is obtained by multiplying the decomposed reflectance and the enhanced illumination. Experiments on severa challenging low-light image datasets show that Retinex-SIE proposed in this paper can better handle low-light images with uneven illumination distribution and avoid problems such as excessive enhancement or insufficient detail enhancement.

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Jiachang Yang, Qin Cheng, and Jianming Liu "Retinex-SIE: self-supervised low-light image enhancement method based on Retinex and homomorphic filtering transformation", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126101J (28 April 2023); https://doi.org/10.1117/12.2671157

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KEYWORDS

Image enhancement

Light sources and illumination

Reflectivity

Education and training

Image restoration

Image filtering

Image quality

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