IEICE TRANSACTIONS on Information
An ICA-Domain Shrinkage Based Poisson-Noise Reduction Algorithm and Its Application to Penumbral Imaging
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E88-D No.4 pp.750-757
- Publication Date
- 2005/04/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietisy/e88-d.4.750
- Type of Manuscript
- PAPER
- Category
- Image Processing and Video Processing
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Xian-Hua HAN, Zensho NAKAO, Yen-Wei CHEN, Ryosuke KODAMA, "An ICA-Domain Shrinkage Based Poisson-Noise Reduction Algorithm and Its Application to Penumbral Imaging" in IEICE TRANSACTIONS on Information,
vol. E88-D, no. 4, pp. 750-757, April 2005, doi: 10.1093/ietisy/e88-d.4.750.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.4.750/_p
Copy
@ARTICLE{e88-d_4_750,
author={Xian-Hua HAN, Zensho NAKAO, Yen-Wei CHEN, Ryosuke KODAMA, },
journal={IEICE TRANSACTIONS on Information},
title={An ICA-Domain Shrinkage Based Poisson-Noise Reduction Algorithm and Its Application to Penumbral Imaging},
year={2005},
volume={E88-D},
number={4},
pages={750-757},
abstract={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.},
keywords={},
doi={10.1093/ietisy/e88-d.4.750},
ISSN={},
month={April},}
Copy
TY - JOUR
TI - An ICA-Domain Shrinkage Based Poisson-Noise Reduction Algorithm and Its Application to Penumbral Imaging
T2 - IEICE TRANSACTIONS on Information
SP - 750
EP - 757
AU - Xian-Hua HAN
AU - Zensho NAKAO
AU - Yen-Wei CHEN
AU - Ryosuke KODAMA
PY - 2005
DO - 10.1093/ietisy/e88-d.4.750
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2005
AB - 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.
ER -
English
