Related Work on Image Quality Assessment

TL;DR

This paper reviews the latest algorithms in image quality assessment, which is crucial for evaluating images affected by various degradations during processing and transmission.

Contribution

It provides a comprehensive overview of current IQA algorithms across different reference categories, highlighting recent advancements.

Findings

Summarizes state-of-the-art IQA methods

Categorizes IQA approaches into FR, RR, and NR

Highlights recent progress in IQA algorithms

Abstract

Due to the existence of quality degradations introduced in various stages of visual signal acquisition, compression, transmission and display, image quality assessment (IQA) plays a vital role in image-based applications. According to whether the reference image is complete and available, image quality evaluation can be divided into three categories: Full-Reference(FR), Reduced- Reference(RR), and Non- Reference(NR). This article will review the state-of-the-art image quality assessment algorithms.