WAVELET PROCESSING OF IMAGES FOR TARGET DETECTION

This article has as its goal the development and test and evaluation o f wavelet-based algorithms for automatically detecting unknown anomali es in two-dimensional images. the general idea behind the work is that the class of wavelet transforms induces a so-called muitiresolution a nalysis (MRA) in image space whereby the image of interest is naturall y decomposed into a sequence of images of varying resolution (from coa rse to fine resolution) in a computationally efficient manner. The ano maly detection can then be performed sequentially beginning at a coars e scale (low resolution) and proceeding to finer scales as needed. The wavelet representation thus effectively allows the user to zoom in on particular areas of interest acid thus detect image anomalies in a ve ry efficient manner.