3 papers
cs.CV2025
Rethinking Model Redundancy for Low-light Image Enhancement
Tong Li, Lizhi Wang, Hansen Feng +3
Low-light image enhancement (LLIE) is a fundamental task in computational photography, aiming to improve illumination, reduce noise, and enhance the image quality of low-light imag…
cs.CV2025
Complementary Advantages: Exploiting Cross-Field Frequency Correlation for NIR-Assisted Image Denoising
Yuchen Wang, Hongyuan Wang, Lizhi Wang +4
Existing single-image denoising algorithms often struggle to restore details when dealing with complex noisy images. The introduction of near-infrared (NIR) images offers new possi…
cs.CV2025
Positive2Negative: Breaking the Information-Lossy Barrier in Self-Supervised Single Image Denoising
Tong Li, Lizhi Wang, Zhiyuan Xu +3
Image denoising enhances image quality, serving as a foundational technique across various computational photography applications. The obstacle to clean image acquisition in real s…