Presentation 2006-06-23
A note on restoration of missing areas in still images using ER Algorithm : Introduction of new constraints using kernel principal component analysis
Takahiro OGAWA, Miki HASEYAMA,
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Abstract(in English) This paper proposes an accurate reconstruction method of missing textures in still images using an ER algorithm. It is assumed that, in the same texture image, different local areas have similar images and Fourier transform magnitudes mapped into a high-dimensional feature space each other. Further, the proposed method sets the constraints of the ER algorithm in such a way that the target local image and its Fourier transform magnitude mapped into the feature space are respectively in their eigenspaces generated from the known local areas in the target image. Then, the proposed method realizes the accurate calculation of the unknown Fourier transform magnitude and its phase of the target local area, so that the missing areas can be restored accurately.
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Keyword(in English) Image / Restoration / ER Algorithm / PCA / Kernel
Paper # CAS2006-9,VLD2006-22,SIP2006-32
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Conference Information
Committee SIP
Conference Date 2006/6/16(1days)
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Registration To Signal Processing (SIP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A note on restoration of missing areas in still images using ER Algorithm : Introduction of new constraints using kernel principal component analysis
Sub Title (in English)
Keyword(1) Image
Keyword(2) Restoration
Keyword(3) ER Algorithm
Keyword(4) PCA
Keyword(5) Kernel
1st Author's Name Takahiro OGAWA
1st Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University()
2nd Author's Name Miki HASEYAMA
2nd Author's Affiliation Graduate School of Information Science and Technology, Hokkaido University
Date 2006-06-23
Paper # CAS2006-9,VLD2006-22,SIP2006-32
Volume (vol) vol.106
Number (no) 116
Page pp.pp.-
#Pages 6
Date of Issue