@inproceedings{41aff4c5636e4f55a6978a911bd1f625,
title = "Zero-LEINR: Zero-Reference Low-light Image Enhancement with Intrinsic Noise Reduction",
abstract = "Zero-reference deep learning-based methods for low-light image enhancement sufficiently mitigate the difficulty of paired data collection while keeping the great generalization on various lighting conditions. However, color bias and unin-tended intrinsic noise amplification are still issues that remain unsolved. This paper proposes a zero-reference end-to-end two-stage network (Zero-LEINR) for low-light image enhancement with intrinsic noise reduction. In the first stage, we introduce a Color Preservation and Light Enhancement Block (CPLEB) that consists of a dual branch structure with different constraints to correct the brightness and preserve the correct color tone. In the second stage, Enhanced-Noise Reduction Block (ENRB) is applied to remove the intrinsic noises being enhanced during the first stage. Due to the zero-reference two-stage structure, our method is generalized to enhance low-light images with correct color tone on unseen datasets and reduce the intrinsic noise simultaneously.",
keywords = "Image denoising, Image processing, Low-light image enhancement, Unsupervised learning",
author = "Tang, {Wing Ho} and Hsuan Yuan and Chiang, {Tzu Hao} and Huang, {Ching Chun}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 56th IEEE International Symposium on Circuits and Systems, ISCAS 2023 ; Conference date: 21-05-2023 Through 25-05-2023",
year = "2023",
doi = "10.1109/ISCAS46773.2023.10181743",
language = "English",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings",
address = "United States",
}