Detection of anomalies in an image by wavelet analysis

Mahmoud Allam; Jun Zhang

doi:10.1117/12.162080

1 November 1993 Detection of anomalies in an image by wavelet analysis

Mahmoud Allam, Jun Zhang

Proceedings Volume 2034, Mathematical Imaging: Wavelet Applications in Signal and Image Processing; (1993) https://doi.org/10.1117/12.162080
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

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.

Citation Download Citation

Mahmoud Allam and Jun Zhang "Detection of anomalies in an image by wavelet analysis", Proc. SPIE 2034, Mathematical Imaging: Wavelet Applications in Signal and Image Processing, (1 November 1993); https://doi.org/10.1117/12.162080

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