Presentation 2010-11-15
Denoising of MR Images Using FREBAS Collaborative Filtering
Masayuki HIZUME, Satoshi ITO, Yoshifumi YAMADA,
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Abstract(in English) We propose a novel image denoising strategy based on the correlation in the FREBAS transformed domain. FREAS transform is a kind of multi-resolution image analysis which consists of two different Fresnel transforms. It can decompose images into down-scaled images having the same size and having different frequency bandwidth. Since these decomposed images have similar distribution for the same direction from the center of FREBAS domain. Even the FEBAS signal is hidden in the noise in low SNR image cases, the signal distribution can be estimated using the distribution of the FREBAS signal located nearby the interested position. We develop an collaborative Wiener filter in the FREBAS transformed domain which implement the collaboration of standard deviation of interested position and that of analogous positions. The experimental results demonstrate that the proposed algorithm improve the SNR in terms of both total SNR and SNR on the edge of images.
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Keyword(in English) Fresnel Transform / Multi-Resolution Analysis / Wiener filter / NLM filter
Paper # MI2010-74
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Conference Information
Committee MI
Conference Date 2010/11/8(1days)
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Paper Information
Registration To Medical Imaging (MI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Denoising of MR Images Using FREBAS Collaborative Filtering
Sub Title (in English)
Keyword(1) Fresnel Transform
Keyword(2) Multi-Resolution Analysis
Keyword(3) Wiener filter
Keyword(4) NLM filter
1st Author's Name Masayuki HIZUME
1st Author's Affiliation Department of Information Systems Sciences, Utsunomiya University()
2nd Author's Name Satoshi ITO
2nd Author's Affiliation Department of Information Systems Sciences, Utsunomiya University
3rd Author's Name Yoshifumi YAMADA
3rd Author's Affiliation Utsunomiya University
Date 2010-11-15
Paper # MI2010-74
Volume (vol) vol.110
Number (no) 280
Page pp.pp.-
#Pages 5
Date of Issue