Blind image restoration method by PCA-based subspace generation
Principal Component Analysis (PCA) has been effectively applied for image restoration. Original idea underlying PCA approach has two different roots. One is from the fact that PCA is relevant to variance of pixel intensity by which the missing high frequency components in blurred image should be rec...
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| Format: | Conference or Workshop Item |
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2015
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| _version_ | 1796861182875795456 |
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| author | Sumali, Brian Hamada, Nozomu Mitsukura, Yasue |
| author_facet | Sumali, Brian Hamada, Nozomu Mitsukura, Yasue |
| author_sort | Sumali, Brian |
| collection | ePrints |
| description | Principal Component Analysis (PCA) has been effectively applied for image restoration. Original idea underlying PCA approach has two different roots. One is from the fact that PCA is relevant to variance of pixel intensity by which the missing high frequency components in blurred image should be recovered. The other comes from the idea of source separation based on PCA. In the light of PCA approach we have proposed an image restoration algorithm which contains the following three novel aspects: iterative application of PCA, Gaussian smoothing filtering for image ensemble creation, and no-reference image quality index for iteration number management. This paper aims to investigate and propose a non-iterative PCA-based image restoration with some generalizations. First, through conducted experiments the variance of Gaussian filters as well as the number of created images by them are appropriately determined. Second, weights are introduced to the principal component images. Finally, optimal weights are determined by maximizing the image quality index with no reference. Experimental results by the proposed method provide higher PSNR than the previous iterative PCA approach. |
| first_indexed | 2024-03-05T19:52:29Z |
| format | Conference or Workshop Item |
| id | utm.eprints-61971 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:52:29Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | utm.eprints-619712017-08-14T08:52:52Z http://eprints.utm.my/61971/ Blind image restoration method by PCA-based subspace generation Sumali, Brian Hamada, Nozomu Mitsukura, Yasue TK7885-7895 Computer engineer. Computer hardware Principal Component Analysis (PCA) has been effectively applied for image restoration. Original idea underlying PCA approach has two different roots. One is from the fact that PCA is relevant to variance of pixel intensity by which the missing high frequency components in blurred image should be recovered. The other comes from the idea of source separation based on PCA. In the light of PCA approach we have proposed an image restoration algorithm which contains the following three novel aspects: iterative application of PCA, Gaussian smoothing filtering for image ensemble creation, and no-reference image quality index for iteration number management. This paper aims to investigate and propose a non-iterative PCA-based image restoration with some generalizations. First, through conducted experiments the variance of Gaussian filters as well as the number of created images by them are appropriately determined. Second, weights are introduced to the principal component images. Finally, optimal weights are determined by maximizing the image quality index with no reference. Experimental results by the proposed method provide higher PSNR than the previous iterative PCA approach. 2015 Conference or Workshop Item PeerReviewed Sumali, Brian and Hamada, Nozomu and Mitsukura, Yasue (2015) Blind image restoration method by PCA-based subspace generation. In: 2015 International Symposium on Intelligent Signal Processing and Communication Systems, 9-12 Nov, 2015, Indonesia. http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=35626 |
| spellingShingle | TK7885-7895 Computer engineer. Computer hardware Sumali, Brian Hamada, Nozomu Mitsukura, Yasue Blind image restoration method by PCA-based subspace generation |
| title | Blind image restoration method by PCA-based subspace generation |
| title_full | Blind image restoration method by PCA-based subspace generation |
| title_fullStr | Blind image restoration method by PCA-based subspace generation |
| title_full_unstemmed | Blind image restoration method by PCA-based subspace generation |
| title_short | Blind image restoration method by PCA-based subspace generation |
| title_sort | blind image restoration method by pca based subspace generation |
| topic | TK7885-7895 Computer engineer. Computer hardware |
| work_keys_str_mv | AT sumalibrian blindimagerestorationmethodbypcabasedsubspacegeneration AT hamadanozomu blindimagerestorationmethodbypcabasedsubspacegeneration AT mitsukurayasue blindimagerestorationmethodbypcabasedsubspacegeneration |