Image quality measures and their performance
Abstract
A number of quality measures are evaluated for gray scale image compression. They are all bivariate, exploiting the differences between corresponding pixels in the original and degraded images. It is shown that although some numerical measures correlate well with the observers' response for a given compression technique, they are not reliable for an evaluation across different techniques. A graphical measure called Hosaka plots, however, can be used to appropriately specify not only the amount, but also the type of degradation in reconstructed images.
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A frame-by-frame image quality assessment (IQA) approach often fails to correlate with subjective ratings of video quality.
“However, such a frame-by-frame IQA approach often fails to correlate with the subjective ratings of quality.1,2”
From ViS3: an algorithm for video quality assessment via analysis of spatial and spatiotemporal slices (2014) · cites this paper as [2]
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- Authors
- Eskicioglu, A. M., & Fisher, P. S.
- Affiliations
- University of North Texas (US)
- Venue
- IEEE Transactions on Communications
- Published
- 1995
- Volume
- 43
- Issue
- 12
- Pages
- 2959-2965
- ISSN
- 0090-6778 (ISSN-L)
- OpenAlex
- W2153777140
- Cited by
- 2,117
- References
- 0
- Citations by year
- 2026: 137 · 2025: 197 · 2024: 191 · 2023: 133 · 2022: 111 · 2021: 90 · 2020: 84 · 2019: 70 · 2018: 76 · 2017: 70 · 2016: 70 · 2015: 85 · 2014: 91 · 2013: 87 · 2012: 84
- FWCI
- 4.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Communications (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Data Compression Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Keywords
- image quality metrics, pixel difference, observer responses, image degradation, quality assessment
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