Human visual perception-based image quality analyzer for assessment of contrast enhancement methods
Author
Source
The International Arab Journal of Information Technology
Issue
Vol. 13, Issue 2 (31 Mar. 2016)8 p.
Publisher
Publication Date
2016-03-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Absoltue mean Brightness Error (AMBE) and entropy are two popular Image Quality Analyzer (IQA) metrics used for assessment of Histogram Equalization (HE)-based contrast enhancement methods.
However, recent study shows that they have poor correlation with Human Visual Perception (HVP); Pearson Correlation Coefficient (PCC) < 0.
4.
This paper, proposed a new IQA which takes into account important properties of HVP with respect to luminance, texture and scale.
evaluation results show that the proposed IQA has significantly improved performance (PCC > 0.
9).
It outperforms all IQAs in study, including two prominent IQAs designed for assessment of image fidelity in image coding-multi-scale structural similarity and information fidelity criterion.
American Psychological Association (APA)
Chen, Soong. 2016. Human visual perception-based image quality analyzer for assessment of contrast enhancement methods. The International Arab Journal of Information Technology،Vol. 13, no. 2.
https://search.emarefa.net/detail/BIM-580987
Modern Language Association (MLA)
Chen, Soong. Human visual perception-based image quality analyzer for assessment of contrast enhancement methods. The International Arab Journal of Information Technology Vol. 13, no. 2 (Mar. 2016).
https://search.emarefa.net/detail/BIM-580987
American Medical Association (AMA)
Chen, Soong. Human visual perception-based image quality analyzer for assessment of contrast enhancement methods. The International Arab Journal of Information Technology. 2016. Vol. 13, no. 2.
https://search.emarefa.net/detail/BIM-580987
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-580987