Using nonlinear wavelet compression to enhance image registration
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We present a method for automatically registering images based on nonlinear compression. The method involves three steps: (i) analysis of the complexity of the images, (ii) high level compression for extracting control points in the images, (iii) registration of the images by matching control points. The first step analyzes the complexity of the given images. It numerically computes from any image a complexity index which determines the efficiency at which the image can be compressed. This index is used in the second step of the algorithm to select coefficients in the wavelet representation of the image to produce a highly compressed image. The wavelet coefficients of the highly compressed image are then transformed to pixel values. Only a few pixel values are nontrivial. The third stage of the algorithm uses a point alignment technique to identify matching control points and to erect the registering transformations. The algorithm is tested on two quite different scenes: a portrait, representing an uncomplicated scene, and a Landsat TM image of the Pacific Northwest. In both cases, images are tested which differ by a rotation and which differ by a rigid transformation. The algorithm allows a choice of different metrics in which to do the compression and selection of control points.