4 accepted papers
Low-light image enhancement aims to improve lightness and eliminate degradation caused by low light. However, most current methods struggle to effectively handle the mixed degradations of both brightness and structure, leading to structural distortions and insufficient brightness enhancement. Additi…
Low-light image enhancement aims to improve visual quality under challenging lighting conditions while preserving details and color fidelity. Existing traditional algorithms and deep learning approaches, often struggle with balancing brightness enhancement and detail preservation, leading to issues…
Image degradation results from a combination of factors. Recently, CNN-based image deblurring methods have made significant progress, but they rely heavily on the accuracy of paired data, which is impractical to collect for every camera. To address this, we propose a physical model for natural image…
Due to dark environments, optical aberrations, etc, the remote sensing images are often submerged under low contrast degradation, which greatly hinders their practical applications for agricultural management and other related tasks. The surface features of remote sensing images are often continuous…