Presentation 1998/6/18
Blind deconvolution of blurred images by Independent Component Analysis
Shinji Umeyama,
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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
Conference Date 1998/6/18(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
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