The goal of no-reference objective image quality assessment (NR-IQA) is to develop a
computational model that can predict the human-perceived quality of distorted images …

Present day no-reference/no-reference image quality assessment (NR IQA) algorithms
usually assume that the distortion affecting the image is known. This is a limiting assumption …

Image quality assessment (IQA) aims to use computational models to measure the image
quality consistently with subjective evaluations. The well-known structural similarity index …

In this paper we propose a new no-reference (NR) image quality assessment (IQA) metric
using the recently revealed free-energy-based brain theory and classical human visual …

This paper addresses the problem of general-purpose No-Reference Image Quality
Assessment (NR-IQA) with the goal of developing a real-time, cross-domain model that can …

An important aim of research on the blind image quality assessment (IQA) problem is to
devise perceptual models that can predict the quality of distorted images with as little prior …

The state-of-the-art general-purpose no-reference image or video quality assessment (NR-
I/VQA) algorithms usually rely on elaborated hand-crafted features which capture the Natural …

In recent years, no-reference/blind image quality assessment (NR-IQA), as a fundamental
but challenging research problem, has been attracting significant attention in the field of …

A new methodology for objective image quality assessment (IQA) with multi-method fusion
(MMF) is presented in this paper. The research is motivated by the observation that there is …

Image quality assessment (IQA) algorithms aim to predict perceived image quality by human
observers. Over the last two decades, a large amount of work has been carried out in the …