# RedHat 9 (Linux i386) - man page for pdl::imagend (redhat section 3)

ImageND(3) User Contributed Perl Documentation ImageND(3)PDL::ImageND - useful image processing routines which work in N-dimensionsNAMEIn some cases (though not as many as one would like) it is possible to write general routines that operate on N-dimensional objects. An example in this module is a N-Dim convolution algorithm I made up one day - it works but the boundary condtions are a bit funny.DESCRIPTIONuse PDL::ImageND;SYNOPSISconvolve Signature: (a(m); b(n); int adims(p); int bdims(q); [o]c(m)) N-dimensional convolution algorithm. $new = convolve $a, $kernel Convolve an array with a kernel, both of which are N-dimensional. Note because of the algorithm used (writing N-dim routines is not easy on the brain!) the boundary conditions are a bit strange. They wrap, but up to the NEXT row/column/cube-slice/etc. If this is a problem consider using zero-padding or something. ninterpol() N-dimensional interpolation routine Signature: ninterpol(point(),data(n),[o]value()) $value = ninterpol($point, $data); "ninterpol" uses "interpol" to find a linearly interpolated value in N dimensions, assuming the data is spread on a uniform grid. To use an arbitrary grid distribution, need to find the grid-space point from the indexing scheme, then call "ninterpol"FUNCTIONSthis is far from triv- ial (and ill-defined in general). rebin Signature: (a(m); [o]b(n); int ns => n) N-dimensional rebinning algorithm $new = rebin $a, $dim1, $dim2,..;. $new = rebin $a, $template; $new = rebin $a, $template, {Norm => 1}; Rebin an N-dimensional array to newly specified dimensions. Specifying `Norm' keeps the sum constant, otherwise the intensities are kept constant. If more template dimensions are given than for the input pdl, these dimensions are created; if less, the final dimensions are maintained as they were. So if $a is a 10 x 10 pdl, then "rebin($a,15)" is a 15 x 10 pdl, while "rebin($a,15,16,17)" is a 15 x 16 x 17 pdl (where the values along the final dimension are all identical). circ_mean_p Calculates the circular mean of an n-dim image and returns the projection. Optionally takes the center to be used. $cmean=circ_mean_p($im); $cmean=circ_mean_p($im,{Center => [10,10]}); circ_mean Smooths an image by applying circular mean. Optionally takes the center to be used. circ_mean($im); circ_mean($im,{Center => [10,10]});--Copyright (C) Karl Glazebrook 1997. All rights reserved. There is no warranty. You are allowed to redistribute this software / documenta- tion under certain conditions. For details, see the file COPYING in the PDL distribution. If this file is separated from the PDL distribu- tion, the copyright notice should be included in the file.AUTHORSperl v5.8.02003-01-29 ImageND(3)