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We present a wavelet-based, high performance, hierarchical scheme for image matching which includes 1) dynamic detection of interesting points as feature points at different levels of subband images via wavelet transform, 2) adaptive thresholding selection based on compactness measures of fuzzy sets in image feature space, and 3) a guided searching strategy for the best matching from coarse level to fine level. In contrast to the traditional parallel approaches which rely on specializeddoi:10.1109/83.862635 pmid:18262992 fatcat:xkyvc6rn2vffvebahqcvqnxmny