Images captured under poor illumination conditions often exhibit characteristics such as low
brightness, low contrast, a narrow gray range, and color distortion, as well as considerable …

Low-light image (LLI) enhancement is an important image processing task that aims at
improving the illumination of images taken under low-light conditions. Recently, a …

Retinex model-based methods have shown to be effective in layer-wise manipulation with
well-designed priors for low-light image enhancement. However, the commonly used hand …

Existing low-light image enhancement techniques are mostly not only difficult to deal with
both visual quality and computational efficiency but also commonly invalid in unknown …

As a vital image enhancement technology, infrared and visible image fusion aims to
generate high-quality fused images with salient targets and abundant texture in extreme …

Low-light image enhancement (LLIE) aims at improving the perception or interpretability of
an image captured in an environment with poor illumination. Recent advances in this area …

Low-light image enhancement plays very important roles in low-level vision areas. Recent
works have built a great deal of deep learning models to address this task. However, these …

Abstract Low-light Image Enhancement (LIE) aims at improving contrast and restoring
details for images captured in low-light conditions. Most of the previous LIE algorithms adjust …

The following three factors restrict the application of existing low-light image enhancement
methods: unpredictable brightness degradation and noise, inherent gap between metric …

Low-light images suffer from low contrast and unclear details, which not only reduces the
available information for humans but limits the application of computer vision algorithms …