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Proceedings Paper

Spatial correlation thresholding-based edge-preserving image restoration
Author(s): Paul Bao; Lei Zhang
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Paper Abstract

It is of great importance in image restoration to remove noise while preserving and enhancing edges. This paper presents a spatial correlation thresholding scheme for image restoration. The dyadic wavelet transform that acts as a Canny edge detector is employed here to characterize the significant structures, which would be strongly correlated along the wavelet scales. A correlation function is defined as the multiplication of two adjacent wavelet subbands with a translation to maximize the mathematical expectation. In the correlation function, edge structures are more discriminable because they are amplified while noise being diluted. Unlike most of the traditional schemes that threshold directly the wavelet coefficients, the proposed scheme applies thresholding on the correlation function to better preserve edges while suppressing noise. A robust threshold is presented and the experiment shows that the proposed scheme outperforms the traditional thresholding schemes not only in SNR comparison but also in the edge preservation.

Paper Details

Date Published: 28 January 2002
PDF: 12 pages
Proc. SPIE 4541, Image and Signal Processing for Remote Sensing VII, (28 January 2002); doi: 10.1117/12.454167
Show Author Affiliations
Paul Bao, Hong Kong Polytechnic Univ. (Hong Kong)
Lei Zhang, Hong Kong Polytechnic Univ. (Hong Kong)

Published in SPIE Proceedings Vol. 4541:
Image and Signal Processing for Remote Sensing VII
Sebastiano Bruno Serpico, Editor(s)

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