IVCVNov 11, 2021

Related Work on Image Quality Assessment

arXiv:2111.06291v2
AI Analysis

It provides a survey for researchers and practitioners in image processing, but it is incremental as it reviews existing work without introducing new methods.

This paper reviews state-of-the-art image quality assessment algorithms, categorizing them into Full-Reference, Reduced-Reference, and Non-Reference methods based on the availability of reference images.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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