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- function varargout = spm_bsplins(varargin)
- % Sample a volume using B-spline interpolation - a compiled routine
- % FORMAT [f,dfx,dfy,dfz] = spm_bsplins(c,x,y,z,d)
- % c - volume of B-spline coefficients (from spm_bsplinc)
- % x,y,z - co-ordinates of sampled points
- % d(1:3) - degree of B-spline (from 0 to 7) along different dimensions
- % - these must be same as used by spm_bsplinc
- % d(4:6) - 1/0 to indicate wrapping along the dimensions
- % f - sampled data
- % dfx,dfy,dfz - sampled first derivatives
- %
- % This function takes B-spline basis coefficients from spm_bsplinc,
- % and re-convolves them with B-splines centred at the new sample points.
- %
- % Note that nearest neighbour interpolation is used instead of 0th
- % degree B-splines, and the derivatives of trilinear interpolation are
- % returned insted of those of 1st degree B-splines. The difference is
- % extremely subtle.
- %
- %_______________________________________________________________________
- %
- % References:
- % M. Unser, A. Aldroubi and M. Eden.
- % "B-Spline Signal Processing: Part I-Theory,"
- % IEEE Transactions on Signal Processing 41(2):821-832 (1993).
- %
- % M. Unser, A. Aldroubi and M. Eden.
- % "B-Spline Signal Processing: Part II-Efficient Design and
- % Applications,"
- % IEEE Transactions on Signal Processing 41(2):834-848 (1993).
- %
- % M. Unser.
- % "Splines: A Perfect Fit for Signal and Image Processing,"
- % IEEE Signal Processing Magazine, 16(6):22-38 (1999)
- %
- % P. Thevenaz and T. Blu and M. Unser.
- % "Interpolation Revisited"
- % IEEE Transactions on Medical Imaging 19(7):739-758 (2000).
- %_______________________________________________________________________
- % Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
- % John Ashburner
- % $Id: spm_bsplins.m 2696 2009-02-05 20:29:48Z guillaume $
- %-This is merely the help file for the compiled routine
- error('spm_bsplins.c not compiled - see Makefile');
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