Perceptual quality assessment plays a vital role in the visual communication systems owing
to the existence of quality degradations introduced in various stages of visual signal …

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 …

Noise causes unpleasant visual effects in low-light image/video enhancement. In this paper,
we aim to make the enhancement model and method aware of noise in the whole process …

Low-light image enhancement is important for high-quality image display and other visual
applications. However, it is a challenging task as the enhancement is expected to improve …

The total variation (TV) regularization model for image restoration is widely utilized due to its
edge preservation properties. Despite its advantages, the TV regularization can obtain …

Recently, due to the strength of deep convolutional neural networks (CNN), many CNN-
based image quality assessment (IQA) models have been studied. However, previous CNN …

Tone mapping operators (TMOs) are developed to convert a high dynamic range (HDR)
image into a low dynamic range (LDR) one for display with the goal of preserving as much …

This paper proposes a novel technique for single image dehazing using adaptive nearest
neighbor regularization to obtain a haze-free transmission map and then approximating the …

The state of the art deep learning based denoising methods can achieve great denoising
results. However, due to the lack of clean training data, the ground truth and noise level are …

We develop a full-reference (FR) video quality assessment framework that integrates
analysis of space–time slices (STSs) with frame-based image quality measurement (IQA) to …