Efficient multidimensional nonlinear but seperable filtering operation. See nlfilt_sep for a basic discussion of the he concept of a nonlinear seperable filters. This is similar, instead applies operations to nonoveralpping blocks (versus a sliding window approach in which all overlapping blocks are considered). Also, as opposed to nlfilt_sep, the output returned by this function is smaller then the input I. The function fun must be able to take an input of the form C=fun(I,radius,param1,...paramk). The return C must be the result of applying the nlfilt operation to the local column (of size 2r+1) of A. For example: % COMPUTES LOCAL BLOCK SUMS (see localsum_block): I = nlfiltblock_sep( I, dims, @rnlfiltblock_sum ); INPUTS I - matrix to compute fun over dims - size of volume to compute fun over fun - nonlinear filter params - optional parameters for nonlinear filter OUTPUTS I - resulting image DATESTAMP 29-Sep-2005 2:00pm See also NLFILT_SEP, RNLFILTBLOCK_SUM