High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range
of exposures, which is important in image processing, computer graphics, and computer …

This paper presents a new solution for low-light image enhancement by collectively
exploiting Signal-to-Noise-Ratio-aware transformers and convolutional models to …

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 …

Though deep learning-based object detection methods have achieved promising results on
the conventional datasets, it is still challenging to locate objects from the low-quality images …

When enhancing low-light images, many deep learning algorithms are based on the Retinex
theory. However, the Retinex model does not consider the corruptions hidden in the dark or …

As the quality of optical sensors improves, there is a need for processing large-scale
images. In particular, the ability of devices to capture ultra-high definition (UHD) images and …

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 …

Convolutional neural networks (CNNs) have achieved significant success in the single
image dehazing task. Unfortunately, most existing deep dehazing models have high …

Challenging illumination conditions (low-light, under-exposure and over-exposure) in the
real world not only cast an unpleasant visual appearance but also taint the computer vision …

Image restoration is a fundamental problem that involves recovering a high-quality clean
image from its degraded observation. All-In-One image restoration models can effectively …