Related Work on Image Quality Assessment
Dongxu Wang

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.
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Taxonomy
TopicsImage and Video Quality Assessment · Advanced Image Fusion Techniques · Advanced Image Processing Techniques
