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 …

In the past two decades, reversible data hiding (RDH), also referred to as lossless or
invertible data hiding, has gradually become a very active research area in the field of data …

Due to the attenuation and scattering of light by water, there are many quality defects in raw
underwater images such as color casts, decreased visibility, reduced contrast, et al.. Many …

As smartphones become people's primary cameras to take photos, the quality of their
cameras and the associated computational photography modules has become a de facto …

We propose a multi-task end-to-end optimized deep neural network (MEON) for blind image
quality assessment (BIQA). MEON consists of two sub-networks-a distortion identification …

This paper presents a perception-aware decomposition and fusion framework for
underwater image enhancement (UIE). Specifically, a general structural patch …

In this paper, we investigate into the problem of image quality assessment (IQA) and
enhancement via machine learning. This issue has long attracted a wide range of attention …

The performance of objective image quality assessment (IQA) models has been evaluated
primarily by comparing model predictions to human quality judgments. Perceptual datasets …

Blind image quality assessment (BIQA) research aims to develop a perceptual model to
evaluate the quality of distorted images automatically and accurately without access to the …

In rate-distortion optimization, the encoder settings are determined by maximizing a
reconstruction quality measure subject to a constraint on the bitrate. One of the main …