Presentation | 1998/6/18 Blind deconvolution of blurred images by Independent Component Analysis Shinji Umeyama, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Independent Component Analysis is a new data analysis method, and its computation algorithms and applications are widely studied recently. Most applications, however, are for the field of one-dimensional data analysis, e. g. sound data analysis, and few applications for two-dimensinal data (e. g., image data) are studied. In this paper, we give a new application of ICA for the two-dimensinal data analysis, which is an image restoration of the blurred images. The proposed method can restore the original image without knowing the blurring process. We can also show that the restoration will be improved significantly if we constrain the blurring process to be centrosymmetric. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | ICA / image restoration / blind deconvolution / blurred image / cumulant / centrosymmetric |
Paper # | PRMU98-27 |
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Conference Information | |
Committee | PRMU |
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Conference Date | 1998/6/18(1days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | |
Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Blind deconvolution of blurred images by Independent Component Analysis |
Sub Title (in English) | |
Keyword(1) | ICA |
Keyword(2) | image restoration |
Keyword(3) | blind deconvolution |
Keyword(4) | blurred image |
Keyword(5) | cumulant |
Keyword(6) | centrosymmetric |
1st Author's Name | Shinji Umeyama |
1st Author's Affiliation | Electrotechnical Laboratory() |
Date | 1998/6/18 |
Paper # | PRMU98-27 |
Volume (vol) | vol.98 |
Number (no) | 126 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |