Presentation 2011-06-02
Image Coding by Compressive Sensing by using Relationship between Texture and Structure Component
Chihiro SUZUKI, Takamichi MIYATA, Yoshinori SAKAI,
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Abstract(in English) Compressing texture features of natural images by conventional JPEG method requires many bits to preserve their feature details. Therefore, the highly compressed JPEG image does not have detailed texture. We define this degraded image without texture features as structure image, and also defined the difference between the input image and the structure image as texture image. In general, one can find the tight relationship between the edges of the structure image and the boundary of texture patterns in the texture image. Moreover, the texture image can be drastically compressed by focusing on the fact that the texture images contains a lot of repetitive features. From these observations, we proposed a novel image coding by using noiselet transform for representing the texture image, and making compaction image that has almost of all repetitive texture patterns. Then, the encoder sends the input image and compaction image compressed by JPEG method, and the noiselet coefficient. At the decoder side, we proposed reconstruction method for the compaction texture image from these information.
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Keyword(in English) Texture Synthesis / Compressive Sensing / Image Coding
Paper # MoMuC2011-2
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Conference Information
Committee MoMuC
Conference Date 2011/5/26(1days)
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Registration To Mobile Multimedia Communications(MoMuC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Image Coding by Compressive Sensing by using Relationship between Texture and Structure Component
Sub Title (in English)
Keyword(1) Texture Synthesis
Keyword(2) Compressive Sensing
Keyword(3) Image Coding
1st Author's Name Chihiro SUZUKI
1st Author's Affiliation Tokyo Institute of Technology()
2nd Author's Name Takamichi MIYATA
2nd Author's Affiliation Tokyo Institute of Technology
3rd Author's Name Yoshinori SAKAI
3rd Author's Affiliation Tokyo Institute of Technology
Date 2011-06-02
Paper # MoMuC2011-2
Volume (vol) vol.111
Number (no) 75
Page pp.pp.-
#Pages 6
Date of Issue