Frequency Domain Information Integrated Network for Low-Light Image Enhancement
Na Li, Xi Luo, Dunlu Peng, Zied Bouraoui
Abstract
Low-light images often suffer from significant noise and detail loss, making it challenging to effectively distinguish signals from noise when processed directly in the spatial domain. To this end, we introduce frequency domain information to better distinguish high-frequency details from low-frequency components, thereby suppressing noise while enhancing details. The proposed method converts sRGB images into raw-RGB images by reversing the Image Signal Processor (ISP) pipeline to avoid unnecessary effects. A frequency information interaction processing unit is then designed to enhance low-frequency textures using high-frequency information and correct high-frequency data through low-frequency information to reduce structural deformation during restoration. The signal-to-noise ratio prior is introduced in the hidden layer to further remove noise. Experimental results show that the proposed method outperforms existing color and structure enhancement methods.
BibTeX
@inproceedings{icassp2025_frequencydomaini,
title = {Frequency Domain Information Integrated Network for Low-Light Image Enhancement},
author = {Na Li and Xi Luo and Dunlu Peng and Zied Bouraoui},
booktitle = {ICASSP 2025},
year = {2025}
}