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Image matching is an inarguably important operation for many practical sophisticated systems in machine vision and medical diagnosis. Many gray-level image matching applications use the sum-of-squared-difference (SSD) or sum-ofabsolute-differences (SAD), which are very sensitive to noise. Almost all images have some kind of noise, which causes the matching tasks significantly difficulty. In this paper we explore a new, less noise sensitive image-matching technique. It uses non linear similaritydoi:10.1007/978-0-387-44641-7_42 dblp:conf/ifip12/IslamK06 fatcat:p6ifp6az7jfn7evrkyeuawdonq