One of the problems associated with the automatic image processing of satellite photographs such as weather maps is the need for image registration; that is, the fitting of a map that has some translational and rotational bias to a known data base. this paper investigates a least square method of image registration using an image that has been converted into a boundary map with a pixel representation of 1 for land, -1 for water and zero for cloud pixels. A sampled correlation array is constructed about the correlation peak of the binary cross-correlation for the coded satellite map against its data base by shifting the satellite map to locations on a given grid, and performing an accumulation of the pixel-by-pixel comparisons between the satellite image and its data base over the whole map or a smaller search window. A least square approximation of the translational and rotational bias can then be performed using the data from this sampled correlation array, fitted against a shape such as an elliptical cone.

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