Nonparametric Quality Assessment Of Natural Images
In this article,the authors explore an alternative way to perform no-reference image quality assessment (NR-IQA). Following a feature extraction stage in which spatial domain statistics are utilized as features,a two-stage nonparametric NR-IQA framework is proposed.This approach requires no training...
Saved in:
Main Author: | |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2016
|
Subjects: | |
Online Access: | http://eprints.utem.edu.my/id/eprint/20967/2/2016%20IEEE%20Multimedia%20-%20NPNO%20BIQA.pdf http://eprints.utem.edu.my/id/eprint/20967/ http://eprints.utem.edu.my/20967/2/2016%20IEEE%20Multimedia%20-%20NPNO%20BIQA.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utem.eprints.20967 |
---|---|
record_format |
eprints |
spelling |
my.utem.eprints.209672021-07-12T03:28:41Z http://eprints.utem.edu.my/id/eprint/20967/ Nonparametric Quality Assessment Of Natural Images Redzuan , Abdul Manap Q Science (General) QA Mathematics In this article,the authors explore an alternative way to perform no-reference image quality assessment (NR-IQA). Following a feature extraction stage in which spatial domain statistics are utilized as features,a two-stage nonparametric NR-IQA framework is proposed.This approach requires no training phase,and it enables prediction of the image distortion type as well as local regions' quality, which is not available in most current algorithms. Experimental results on IQA databases show that the proposed framework achieves high correlation to human perception of image quality and delivers competitive performance to state-of-the-art NR-IQA algorithms. IEEE 2016-10 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/20967/2/2016%20IEEE%20Multimedia%20-%20NPNO%20BIQA.pdf Redzuan , Abdul Manap (2016) Nonparametric Quality Assessment Of Natural Images. IEEE Multimedia, 23. pp. 22-30. ISSN 1070-986X http://eprints.utem.edu.my/20967/2/2016%20IEEE%20Multimedia%20-%20NPNO%20BIQA.pdf |
institution |
Universiti Teknikal Malaysia Melaka |
building |
UTEM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknikal Malaysia Melaka |
content_source |
UTEM Institutional Repository |
url_provider |
http://eprints.utem.edu.my/ |
language |
English |
topic |
Q Science (General) QA Mathematics |
spellingShingle |
Q Science (General) QA Mathematics Redzuan , Abdul Manap Nonparametric Quality Assessment Of Natural Images |
description |
In this article,the authors explore an alternative way to perform no-reference image quality assessment (NR-IQA). Following a feature extraction stage in which spatial domain statistics are utilized as features,a two-stage nonparametric NR-IQA framework is proposed.This approach requires no training phase,and it enables prediction of the image distortion type as well as local regions' quality, which is not available in most current algorithms. Experimental results on IQA databases show that the proposed framework achieves high correlation to human perception of image quality and delivers competitive performance to state-of-the-art NR-IQA algorithms. |
format |
Article |
author |
Redzuan , Abdul Manap |
author_facet |
Redzuan , Abdul Manap |
author_sort |
Redzuan , Abdul Manap |
title |
Nonparametric Quality Assessment Of Natural Images |
title_short |
Nonparametric Quality Assessment Of Natural Images |
title_full |
Nonparametric Quality Assessment Of Natural Images |
title_fullStr |
Nonparametric Quality Assessment Of Natural Images |
title_full_unstemmed |
Nonparametric Quality Assessment Of Natural Images |
title_sort |
nonparametric quality assessment of natural images |
publisher |
IEEE |
publishDate |
2016 |
url |
http://eprints.utem.edu.my/id/eprint/20967/2/2016%20IEEE%20Multimedia%20-%20NPNO%20BIQA.pdf http://eprints.utem.edu.my/id/eprint/20967/ http://eprints.utem.edu.my/20967/2/2016%20IEEE%20Multimedia%20-%20NPNO%20BIQA.pdf |
_version_ |
1706960958328406016 |
score |
13.18916 |