An ICA-Domain Shrinkage Based Poisson-Noise Reduction Algorithm and Its Application to Penumbral Imaging(Image Processing and Video Processing)

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概要

• 論文の詳細を見る

• Penumbral imaging is a technique which exploits the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. Since the technique is based on linear deconvolution, it is sensitive to noise. In this paper, a two-step method is proposed for decoding penumbral images : first, a noise-reduction algorithm based on ICA-domain (independent component analysis-domain) shrinkage is applied to smooth the given noise ; second, the conventional linear deconvolution follows. The simulation results show that the reconstructed image is dramatically improved in comparison to that without the noise-removing filters, and the proposed method is successfully applied to real experimental X-ray imaging.

• 社団法人電子情報通信学会の論文
• 2005-04-01

著者

• Han Xianhua

  Graduate School Of Science And Engineering Ritsumeikan University

• Han Xian‐hua

  Ritsumeikan Univ. Kusatsu‐shi Jpn

• Chen Yen

  College Of Information Science And Engineering Ritsumeikan University

• Han Xian

  Faculty Of Engineering University Of The Ryukyus

• Chen Y‐w

  College Of Information Science And Engineering Ritsumeikan University

• Han Xian‐hua

  College Of Information Science And Engineering Ritsumeikan University

• KODAMA Ryosuke

  Institute of Laser Engineering, Osaka University

• NAKAO Zensho

  Faculty of Engineering, University of the Ryukyus

• Nakao Zensho

  Faculty Of Engineering University Of The Ryukyus

• Kodama Ryosuke

  Institute Of Laser Engineering Osaka University

• Han Xianhua

  College of Information Science and Engineering, Ritsumeikan University

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