The Reverse Positioning Refining Algorithm for Auto-matching of the Remote Sensing Images

Image matching is one of the most important and challenging areas in computer vision and remote sensing.Especially for the wide base line images with large distortions,the accuracy and reliability of the matching is a bottleneck in the auto-disposition given the large volume of images.Based on an analysis of the latest refining methods,the Reverse Positioning Refining Algorithm in Matching(REPRAM) composed of REPRAM Excluding and the REPRAM Including parts is proposed.The theory and properties are discussed in relation to the refining ability for excluding more bads and including more rights,where the mutual impact is separated.Thus,there is no need for extrinsic and intrinsic parameters of the camera or control points.Although the original reliability of the rough couples is about 30 percent,the algorithm works robustly with a high degree of reliability above 99.5 percents under the ranging error threshold for several kinds of remote sensing images as well as for close shot pictures.