Laser & Optoelectronics Progress, Volume. 60, Issue 14, 1410009(2023)

Low-Light Image-Enhancement Algorithm Based on Homomorphic Frequency Division Aggregation

Yali Zhang1, Shaobo Ding1, Changlu Li1、*, Xinming Yao2, and Wenyuan Li1
Author Affiliations
  • 1School of Microelectronics, Tianjin University, Tianjin 300072, China
  • 2Forty-Fifth Research Institute of China Electronics Technology Group Corporation, Beijing 100176, China
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    A weak-light environment leads to low contrast, dark brightness, missing details, and other problems with pictures captured by image acquisition equipment. Therefore, a low illumination image-enhancement algorithm based on homomorphic frequency division aggregation is proposed. First, the transfer function of homomorphic filtering is improved, the original image is decomposed into high- and low-frequency components, and some dark-area details are enhanced without the loss of bright-area details. The improved homomorphic-filtering transfer function has fewer parameters than the original and is easy to adjust. Next, the two components are enhanced. That is, the detail enhancement network is designed to improve the detailed information of the high-frequency part, and the low-light image enhancement via illumination map estimation (LIME) algorithm is used to enhance the brightness of the low-frequency part. Finally, a local adaptive network is designed to jointly fine-tune the high- and low-frequency components of the image to correct the distortion during fusion. The experimental results from the subjective vision and objective evaluation indicators show that the proposed algorithm can effectively balance the enhancement effect of smooth regions and texture components of the image and improve the image visual quality.

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    Yali Zhang, Shaobo Ding, Changlu Li, Xinming Yao, Wenyuan Li. Low-Light Image-Enhancement Algorithm Based on Homomorphic Frequency Division Aggregation[J]. Laser & Optoelectronics Progress, 2023, 60(14): 1410009

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    Paper Information

    Category: Image Processing

    Received: Mar. 22, 2022

    Accepted: Sep. 5, 2022

    Published Online: Jul. 17, 2023

    The Author Email: Li Changlu (3383928167@qq.com)

    DOI:10.3788/LOP221078

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