Scale and translation invariant minimum average correlation energy filter

A new type, to our knowledge, of scale and translation invariant correlation filter is described. Its form in polar coordinates generalizes the forms of the one-decomposition-term filters. That is combined with the minimum-average-correlation-energy optimization method to suppress the sidelobes and achieve correlation peaks. A theoretical analysis as well as a detailed explanation of the computational procedure is provided. The concept is tested on five interferometric images of 256 gray levels without preprocessing. The computed filter gives correlation peaks for reference image scales in the range of 0.3/4.0 (minimal scale: maximal scale = 1:13). The discrimination ability of the filter is investigated-no false peak occurred. The filter works in the background so that there is no need for input image segmentation. A method for extension is described to calculate a filter for more than one reference image.