A simple and effective low-light image enhancement method based on a noise-aware texture-preserving retinex model is proposed in this work. The new method, called NATLE, attempts to strike a balance between noise removal and natural texture preservation through a low-complexity solution. Its cost function includes an estimated piece-wise smooth illumination map and a noise-free texture-preserving reflectance map. Afterwards, illumination is adjusted to form the enhanced image together with the reflectance map. Extensive experiments are conducted on common low-light image enhancement datasets to demonstrate the superior performance of NATLE.
@article{arxiv.2009.01385,
title = {Noise-Aware Texture-Preserving Low-Light Enhancement},
author = {Zohreh Azizi and Xuejing Lei and C. -C Jay Kuo},
journal= {arXiv preprint arXiv:2009.01385},
year = {2020}
}
Comments
Accepted by IEEE VCIP 2020. The final version will appear in IEEE VCIP 2020