Presentation 2007-12-11
A shift-invariant non-negative sparse image representation with estimation of the number of bases
Hidenari NISHIURA, Makoto NAKASHIZUKA, Youji IIGUNI,
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Abstract(in English) A sparse coding is one of the generative model for images, and can obtain bases that indicates features of an image under sparsity condition. In order to perform the decomposition, it is necessary to estimate the number of the bases that are correspond to the micro structures of the image texture. However, it is difficult to estimate the number of the different micro structures from an unknown image. In this paper, we propose an iterative method to estimate the number of the micro structures of the images through the shift-invariant sparse coding. In experiments, the proposed method is applied to the texture image separation. By this experiment, we demonstrated that the proposed method is effective for the representation of the texture images.
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Keyword(in English) estimation of the number of bases / sparse representation / sparse coding / image texture
Paper # SIS2007-58
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Conference Date 2007/12/4(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A shift-invariant non-negative sparse image representation with estimation of the number of bases
Sub Title (in English)
Keyword(1) estimation of the number of bases
Keyword(2) sparse representation
Keyword(3) sparse coding
Keyword(4) image texture
1st Author's Name Hidenari NISHIURA
1st Author's Affiliation Graduate School of Engineering Science, Osaka University()
2nd Author's Name Makoto NAKASHIZUKA
2nd Author's Affiliation Graduate School of Engineering Science, Osaka University
3rd Author's Name Youji IIGUNI
3rd Author's Affiliation Graduate School of Engineering Science, Osaka University
Date 2007-12-11
Paper # SIS2007-58
Volume (vol) vol.107
Number (no) 374
Page pp.pp.-
#Pages 6
Date of Issue