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Single image Super Resolution by no-reference image quality index optimization in PCA subspace

Principal Component Analysis (PCA) has been effectively applied for solving atmospheric-turbulence degraded images. PCA-based approaches improve the image quality by adding high-frequency components extracted using PCA to the blurred image. The PCA-based restoration process is similar with conventio...

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Main Authors: Sumali, B., Sarkan, H., Hamada, N., Mitsukura, Y.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Subjects:
T Technology (General)
Online Access:http://eprints.utm.my/id/eprint/73126/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983517105&doi=10.1109%2fCSPA.2016.7515828&partnerID=40&md5=b67866974e335b257bdbfed1f77276d0
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spelling my.utm.731262017-11-29T23:58:43Z http://eprints.utm.my/id/eprint/73126/ Single image Super Resolution by no-reference image quality index optimization in PCA subspace Sumali, B. Sarkan, H. Hamada, N. Mitsukura, Y. T Technology (General) Principal Component Analysis (PCA) has been effectively applied for solving atmospheric-turbulence degraded images. PCA-based approaches improve the image quality by adding high-frequency components extracted using PCA to the blurred image. The PCA-based restoration process is similar with conventional single-frame Super-Resolution (SR) methods, which perform SR process by improving the edges portion of low-resolution images. This paper aims to introduce PCA-based restoration to solve SR problem with additive white Gaussian noise. We conducted experiments using standard image database and show comparative result with the latest deep-learning SR approach. Institute of Electrical and Electronics Engineers Inc. 2016 Conference or Workshop Item PeerReviewed Sumali, B. and Sarkan, H. and Hamada, N. and Mitsukura, Y. (2016) Single image Super Resolution by no-reference image quality index optimization in PCA subspace. In: 12th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2016, 4 March 2016 through 6 March 2016, Melaka; Malaysia. https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983517105&doi=10.1109%2fCSPA.2016.7515828&partnerID=40&md5=b67866974e335b257bdbfed1f77276d0
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Sumali, B.
Sarkan, H.
Hamada, N.
Mitsukura, Y.
Single image Super Resolution by no-reference image quality index optimization in PCA subspace
description Principal Component Analysis (PCA) has been effectively applied for solving atmospheric-turbulence degraded images. PCA-based approaches improve the image quality by adding high-frequency components extracted using PCA to the blurred image. The PCA-based restoration process is similar with conventional single-frame Super-Resolution (SR) methods, which perform SR process by improving the edges portion of low-resolution images. This paper aims to introduce PCA-based restoration to solve SR problem with additive white Gaussian noise. We conducted experiments using standard image database and show comparative result with the latest deep-learning SR approach.
format Conference or Workshop Item
author Sumali, B.
Sarkan, H.
Hamada, N.
Mitsukura, Y.
author_facet Sumali, B.
Sarkan, H.
Hamada, N.
Mitsukura, Y.
author_sort Sumali, B.
title Single image Super Resolution by no-reference image quality index optimization in PCA subspace
title_short Single image Super Resolution by no-reference image quality index optimization in PCA subspace
title_full Single image Super Resolution by no-reference image quality index optimization in PCA subspace
title_fullStr Single image Super Resolution by no-reference image quality index optimization in PCA subspace
title_full_unstemmed Single image Super Resolution by no-reference image quality index optimization in PCA subspace
title_sort single image super resolution by no-reference image quality index optimization in pca subspace
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2016
url http://eprints.utm.my/id/eprint/73126/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983517105&doi=10.1109%2fCSPA.2016.7515828&partnerID=40&md5=b67866974e335b257bdbfed1f77276d0
_version_ 1643656582640173056
score 13.211869

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