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Proceedings Paper

Detection of anomalies in an image by wavelet analysis
Author(s): Mahmoud Allam; Jun Zhang
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Paper Abstract

In this paper, a wavelet based approach to the detection of anomalies in an image is described. In this approach, the anomalies are detected through hypothesis tests on the wavelet coefficients of the input image. In the development of this approach, some results on the correlation structure of the wavelet expansion of wide-sense stationary (WSS) processes are established. Namely, the wavelet coefficients are WSS and weakly within correlated a resolution level, uncorrelated when separated by more than one resolution levels, almost uncorrelated when separated by one resolution level. Experimental results on both synthetic and real-world images (sandpaper defect detection) and comparison with results obtained by neural network demonstrate the efficacy of the wavelet approach.

Paper Details

Date Published: 1 November 1993
PDF: 12 pages
Proc. SPIE 2034, Mathematical Imaging: Wavelet Applications in Signal and Image Processing, (1 November 1993); doi: 10.1117/12.162080
Show Author Affiliations
Mahmoud Allam, Univ. of Wisconsin/Milwaukee (United States)
Jun Zhang, Univ. of Wisconsin/Milwaukee (United States)


Published in SPIE Proceedings Vol. 2034:
Mathematical Imaging: Wavelet Applications in Signal and Image Processing
Andrew F. Laine, Editor(s)

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