Low-light image enhancement (LLIE) investigates how to improve illumination and produce
normal-light images. The majority of existing methods improve low-light images via a global …

This paper proposes a new framework for low-light image enhancement by simultaneously
conducting the appearance as well as structure modeling. It employs the structural feature to …

Previous raw image-based low-light image enhancement methods predominantly relied on
feed-forward neural networks to learn deterministic mappings from low-light to normally …

As a critical preprocessing technique, low-illumination image enhancement has a wide
range of practical applications. It aims to improve the visual perception of a given image …

This paper presents a novel network structure with illumination-aware gamma correction
and complete image modelling to solve the low-light image enhancement problem. Low …

This paper presents a comprehensive survey of low-light image and video enhancement.
We begin with the challenging mixed over-/under-exposed images, which are under …

The exclusive properties of RAW data have shown great potential for low-light image
enhancement. Nevertheless, the performance is bottlenecked by the inherent limitations of …

The images captured under improper exposure conditions often suffer from contrast
degradation and detail distortion. Contrast degradation will destroy the statistical properties …

Restoring high quality images from raw data in low light is challenging due to various noises
caused by limited photon count and complicated Image Signal Process (ISP). Although …

Nano-color routing has emerged as an immensely popular and widely discussed subject in
the realms of light field manipulation, image sensing, and the integration of deep learning …