Patent ID: 6204853
Filing Date: 2001-03-20
Classification: G06K,G06T,H04N

Abstract:
A method of reducing noise in images while preserving edge information comprising the steps of:a) acquiring a multidimensional set of images S each which vary at least over D dimensions, comprised of a set of voxel values;b) selecting a current voxel at a point p to be filtered;c) determining a plurality of first differences S.sub.i =dS/di at the current voxel, where i represents each of D dimensions;d) determining a plurality of second differences S.sub.ij, from the first differences, where indices i, j represent each of D dimensions;e) determining D-1 tangent vectors e.sub.1, e.sub.2, . . . e.sub.D-1 at point p;f) projecting second differences S.sub.ij onto tangent vectors e.sub.1, e.sub.2, . . . e.sub.D-1 to result in a curvature matrix B.sub..alpha..beta. ;g) diagonalizing curvature matrix B.sub..alpha..beta. to determine a diagonal matrix with diagonal elements being curvatures K.sub.1, K.sub.2, . . . K.sub.D-1 ;h) testing the signs of the curvatures K.sub.1, K.sub.2, . . . K.sub.D-1, and if the curvature signs are the same:i. calculating a cofactor .DELTA..sub.ij from S.sub.ij ;ii. modifying the current voxel value S.sub.w at point p according to: ##EQU11##to result in the new filtered value S.sub.w+1 ; andi) repeating steps ""c"" through ""h"" for a plurality of different voxels as the current voxel in a desired region to perform a filtering iteration resulting in filtered data S.sub.w+1 having reduced noise with little change in detail.