Presentation 2009-02-05
A Note on Adaptive Resolution Enhancement of Still Images Based on SVDD
Takahiro OGAWA, Miki HASEYAMA,
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Abstract(in English) This paper presents a support vector data description (SVDD) based adaptive resolution enhancement of still images. First, the proposed method estimates unknown high-frequency components of a target image in such a way that the distance between the estimation result and the center of hypersphere obtained from training high-resolution (HR) local images by the SVDD becomes minimum. In this scheme, since local images between two different levels of a pyramid structure are similar to each other, local images within the target low resolution (LR) image are utilized as the training data. Furthermore, in order to realize accurate resolution enhancement of images containing several kinds of textures, these training local images are previously clustered, and the above estimation scheme is performed by using the hypersphere of each cluster. In this procedure, the proposed method determines the final output based on the probability defined from the distance between the estimation result and the center of the hypersphere for each cluster. Therefore, this approach provides a solution to a problem of traditional methods of not being able to perform adaptive estimation of the high-frequency components, and accurate resolution enhancement can be expected by our method. Some experimental results are shown to verify the performance of the proposed method.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Resolution enhancement / Image enlargement / Super-resolution / SVDD
Paper # ITS2008-82,IE2008-252
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Conference Information
Committee ITS
Conference Date 2009/1/28(1days)
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Paper Information
Registration To Intelligent Transport Systems Technology (ITS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Note on Adaptive Resolution Enhancement of Still Images Based on SVDD
Sub Title (in English)
Keyword(1) Resolution enhancement
Keyword(2) Image enlargement
Keyword(3) Super-resolution
Keyword(4) SVDD
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 2009-02-05
Paper # ITS2008-82,IE2008-252
Volume (vol) vol.108
Number (no) 424
Page pp.pp.-
#Pages 6
Date of Issue