Detection of anomalies in an image by wavelet analysis
Mahmoud E. Allam, Jun Zhang · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
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.