In this paper, we propose a diffusion-based unsupervised framework that incorporates
physically explainable Retinex theory with diffusion models for low-light image …

In real-world scenarios, image impairments often manifest as composite degradations,
presenting a complex interplay of elements such as low light, haze, rain, and snow. Despite …

Despite substantial progress all-in-one image restoration (IR) grapples with persistent
challenges in handling intricate real-world degradations. This paper introduces MPerceiver …

Abstract Most existing Low-light Image Enhancement (LLIE) methods either directly map
Low-Light (LL) to Normal-Light (NL) images or use semantic or illumination maps as guides …

Low-light images often suffer from information loss and RGB value degradation due to
extremely low or nonuniform lighting conditions. Many existing methods primarily focus on …

Low-light image enhancement (LLIE) has a significant role in edge vision applications
(EVA). Despite its widespread practicability the existing LLIE methods are impractical due to …

Illumination degradation image restoration (IDIR) techniques aim to improve the visibility of
degraded images and mitigate the adverse effects of deteriorated illumination. Among these …

Smart ports utilize an extensive array of surveillance cameras to collect and transmit visual
data for timely port monitoring. Nevertheless, complicated and ever-changing lighting …

While recent low-light image enhancement (LLIE) methods have made significant
advancements, they still face challenges in terms of low visual quality and weak …

Exposure correction tasks are dedicated to recovering the brightness and structural
information of overexposed or underexposed images. The recovery difficulty of areas with …