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Image quality assessment by discrete orthogonal moments

This paper proposes a novel full-reference quality assessment (QA) metric that automatically assesses the quality of an image in the discrete orthogonal moments domain. This metric is constructed by representing the spatial information of an image using low order moments. The computation, up to four...

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Main Authors: Wee, Chong-Yaw., Paramesran, R., Mukundan, R., Jiang, X.
Format: Article
Published: Elsevier 2010
Subjects:
Q Science (General)
Online Access:http://eprints.um.edu.my/11922/
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spelling my.um.eprints.119222015-01-13T06:49:57Z http://eprints.um.edu.my/11922/ Image quality assessment by discrete orthogonal moments Wee, Chong-Yaw. Paramesran, R. Mukundan, R. Jiang, X. Q Science (General) This paper proposes a novel full-reference quality assessment (QA) metric that automatically assesses the quality of an image in the discrete orthogonal moments domain. This metric is constructed by representing the spatial information of an image using low order moments. The computation, up to fourth order moments, is performed on each individual (8 x 8) non-overlapping block for both the test and reference images. Then, the computed moments of both the test and reference images are combined in order to determine the moment correlation index of each block in each order. The number of moment correlation indices used in this study is nine. Next, the mean of each moment correlation index is computed and thereafter the single quality interpretation of the test image with respect to its reference is determined by taking the mean value of the computed means of all the moment correlation indices. The proposed objective metrics based on two discrete orthogonal moments. Tchebichef and Krawtchouk moments, are developed and their performances are evaluated by comparing them with subjective ratings on several publicly available databases. The proposed discrete orthogonal moments based metric performs competitively well with the state-of-the-art models in terms of quality prediction while outperforms them in terms of computational speed. (C) 2010 Elsevier Ltd. All rights reserved. Elsevier 2010 Article PeerReviewed Wee, Chong-Yaw. and Paramesran, R. and Mukundan, R. and Jiang, X. (2010) Image quality assessment by discrete orthogonal moments. Pattern Recognition, 43 (12). pp. 4055-4068.
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic Q Science (General)
spellingShingle Q Science (General)
Wee, Chong-Yaw.
Paramesran, R.
Mukundan, R.
Jiang, X.
Image quality assessment by discrete orthogonal moments
description This paper proposes a novel full-reference quality assessment (QA) metric that automatically assesses the quality of an image in the discrete orthogonal moments domain. This metric is constructed by representing the spatial information of an image using low order moments. The computation, up to fourth order moments, is performed on each individual (8 x 8) non-overlapping block for both the test and reference images. Then, the computed moments of both the test and reference images are combined in order to determine the moment correlation index of each block in each order. The number of moment correlation indices used in this study is nine. Next, the mean of each moment correlation index is computed and thereafter the single quality interpretation of the test image with respect to its reference is determined by taking the mean value of the computed means of all the moment correlation indices. The proposed objective metrics based on two discrete orthogonal moments. Tchebichef and Krawtchouk moments, are developed and their performances are evaluated by comparing them with subjective ratings on several publicly available databases. The proposed discrete orthogonal moments based metric performs competitively well with the state-of-the-art models in terms of quality prediction while outperforms them in terms of computational speed. (C) 2010 Elsevier Ltd. All rights reserved.
format Article
author Wee, Chong-Yaw.
Paramesran, R.
Mukundan, R.
Jiang, X.
author_facet Wee, Chong-Yaw.
Paramesran, R.
Mukundan, R.
Jiang, X.
author_sort Wee, Chong-Yaw.
title Image quality assessment by discrete orthogonal moments
title_short Image quality assessment by discrete orthogonal moments
title_full Image quality assessment by discrete orthogonal moments
title_fullStr Image quality assessment by discrete orthogonal moments
title_full_unstemmed Image quality assessment by discrete orthogonal moments
title_sort image quality assessment by discrete orthogonal moments
publisher Elsevier
publishDate 2010
url http://eprints.um.edu.my/11922/
_version_ 1643689177512935424
score 13.211869

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