Full-Reference and No-reference Image Blur Assessment Based on Edge Information

Blur images are often subjected to the loss of high frequency content during acquisition, compression and multimedia transmission. Hence, objective blur assessment is implemented to identify and quantify image quality degradation by blurriness artifact in order to maintain and control the quality of...

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Main Authors: Bong, D.B.L, Ng, A.S.L
Format: E-Article
Published: Journal on Advanced Science, Engineering and Information Technology 2012
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Online Access:http://ir.unimas.my/id/eprint/3009/
http://www.insightsociety.org/ojaseit/index.php/ijaseit/article/view/161
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spelling my.unimas.ir.30092015-03-24T00:27:46Z http://ir.unimas.my/id/eprint/3009/ Full-Reference and No-reference Image Blur Assessment Based on Edge Information Bong, D.B.L Ng, A.S.L TK Electrical engineering. Electronics Nuclear engineering Blur images are often subjected to the loss of high frequency content during acquisition, compression and multimedia transmission. Hence, objective blur assessment is implemented to identify and quantify image quality degradation by blurriness artifact in order to maintain and control the quality of the images. In this paper, objective full-reference and no-reference blur assessments using edge information are presented with the aim to provide computational models that can automatically measure the amount of blurriness artifact such as Gaussian blur on the images. The amount of Gaussian blur on an image, also known as the final blur measurement is determined by averaging the sum of edge width over all detected edges which satisfy the edge criteria. The final blur measurement for all test images based on full-reference and no-reference implementations are also validated with subjective results. The validation results show that the objective full-reference and no-reference blur assessments correlate closely to perceptual image quality. Journal on Advanced Science, Engineering and Information Technology 2012 E-Article NonPeerReviewed Bong, D.B.L and Ng, A.S.L (2012) Full-Reference and No-reference Image Blur Assessment Based on Edge Information. International Journal on Advanced Science, Engineering and Information Technology, 2 (1). http://www.insightsociety.org/ojaseit/index.php/ijaseit/article/view/161
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Bong, D.B.L
Ng, A.S.L
Full-Reference and No-reference Image Blur Assessment Based on Edge Information
description Blur images are often subjected to the loss of high frequency content during acquisition, compression and multimedia transmission. Hence, objective blur assessment is implemented to identify and quantify image quality degradation by blurriness artifact in order to maintain and control the quality of the images. In this paper, objective full-reference and no-reference blur assessments using edge information are presented with the aim to provide computational models that can automatically measure the amount of blurriness artifact such as Gaussian blur on the images. The amount of Gaussian blur on an image, also known as the final blur measurement is determined by averaging the sum of edge width over all detected edges which satisfy the edge criteria. The final blur measurement for all test images based on full-reference and no-reference implementations are also validated with subjective results. The validation results show that the objective full-reference and no-reference blur assessments correlate closely to perceptual image quality.
format E-Article
author Bong, D.B.L
Ng, A.S.L
author_facet Bong, D.B.L
Ng, A.S.L
author_sort Bong, D.B.L
title Full-Reference and No-reference Image Blur Assessment Based on Edge Information
title_short Full-Reference and No-reference Image Blur Assessment Based on Edge Information
title_full Full-Reference and No-reference Image Blur Assessment Based on Edge Information
title_fullStr Full-Reference and No-reference Image Blur Assessment Based on Edge Information
title_full_unstemmed Full-Reference and No-reference Image Blur Assessment Based on Edge Information
title_sort full-reference and no-reference image blur assessment based on edge information
publisher Journal on Advanced Science, Engineering and Information Technology
publishDate 2012
url http://ir.unimas.my/id/eprint/3009/
http://www.insightsociety.org/ojaseit/index.php/ijaseit/article/view/161
_version_ 1644509241350815744
score 13.209306