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Application of a Noise-Smoothing Filter Based on Adaptive Windowing to Penumbral Imaging
Yen-Wei CHEN Hiroshi ARAKAWA Zensho NAKAO Katsumi YAMASHITA Ryosuke KODAMA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1998/03/25
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Image Theory
penumbral imaging, local-statistic filter, adaptive windowing, signal-dependant noise,
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Penumbral imaging is a technique which uses the facts that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The technique is based on a linear deconvolution. In this paper, a two-step method is proposed for decoding penumbral images. First a local-statistic filter based on adaptive windowing is applied to smooth the noise; then, followed by the conventional linear deconvolution. The simulation results show that the reconstructed image is dramatically improved in comparison to that without the noise-smoothing filtering, and the proposed method is also applied to real experimental X-ray imaging.