A Fusion-Based and Multi-Layer Method for Low Light Image Enhancement
Xueyan Zhou, Jiacen Guo, Hao Liu, Chao Wang
Abstract
The results obtained by many current low light image enhancement algorithms exhibit unnatural effects and insufficient contrast. This paper proposes a low light image enhancement algorithm using a fusion-based and multi-layer model. We decompose the illumination of the input image into high-frequency and low-frequency components. Then, we adjust the illumination using two different correcting functions based on a priori statistics and decompose them iteratively until the final distribution is uniform. Finally, we obtain enhanced results by multiplying all the decomposed reflectance with the last layer of corrected illumination. The experiments show that our proposed method achieves excellent image naturalness, contrast, and quality.
BibTeX
@inproceedings{icassp2023_afusionbasedandm,
title = {A Fusion-Based and Multi-Layer Method for Low Light Image Enhancement},
author = {Xueyan Zhou and Jiacen Guo and Hao Liu and Chao Wang},
booktitle = {ICASSP 2023},
year = {2023}
}