A multi-sensor image registration method adapted for larger scale

A new method based on the edge curvature area extreme-value and the edge correlation for efficient image registration is proposed. First of all, draw some edges from the pending image, set the edge length threshold by using a comparatively large Gauss parameter, save the longer edges only, and mode them with improved Freeman. Secondly, with the Freeman code aforementioned, compute the curvature of the curve, and match the edges according to the corresponding situation of the curve area curvature and get the scale transform parameter. Thirdly, resample the image by using that scale parameter, draw some edges again and by applying the edge correlation and consistency check means, get the corresponding pairs of edges. Finally, by using the Least Mean Square, obtain the registration parameter of the image. This arithmetic applies in situations like registration images with comparatively rotating angles and translational motions.