www.gusucode.com > 声音的处理有:LPC,FFT,共振峰,频谱源码程序 > siganlandsystemusingMatlab/SSUM/filters/image/gauss2d.m
% gauss2d() - generate a 2 dimensional gaussian matrice % % Usage: % >> [ gaussmatrix ] = gauss2d( rows, columns, ... % sigmaR, sigmaC, meanR, meanC, cut) % % Example: % >> gauss2d( 5, 5) % % Inputs: % rows - number of rows % columns - number of columns % sigmaR - standart deviation for rows (default: rows/5) % sigmaC - standart deviation for columns (default: columns/5) % meanR - mean for rows (default: center of the row) % meanC - mean for columns (default: center of the column) % cut - percentage (0->1) of the maximum value for removing % values in the matrix (default: 0) % % Ouput: % gaussmatrix - gaussian matrix % % Author: Arnaud Delorme, CNL / Salk Institute, 2001 %123456789012345678901234567890123456789012345678901234567890123456789012 % Copyright (C) 2001 Arnaud Delorme, Salk Institute, arno@salk.edu % % This program is free software; you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation; either version 2 of the License, or % (at your option) any later version. % % This program is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with this program; if not, write to the Free Software % Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA % $Log: gauss2d.m,v $ % Revision 1.1 2002/04/05 17:39:45 jorn % Initial revision % % 01-25-02 reformated help & license -ad function mat = gauss2d( sizeX, sizeY, sigmaX, sigmaY, meanX, meanY, cut); if nargin < 2 help gauss2d return; end; if nargin < 3 sigmaX = sizeX/5; end; if nargin < 4 sigmaY = sizeY/5; end; if nargin < 5 meanX = (sizeX+1)/2; end; if nargin < 6 meanY = (sizeY+1)/2; end; if nargin < 7 cut = 0; end; X = linspace(1, sizeX, sizeX)'* ones(1,sizeY); Y = ones(1,sizeX)' * linspace(1, sizeY, sizeY); %[-sizeX/2:sizeX/2]'*ones(1,sizeX+1); %Y = ones(1,sizeY+1)' *[-sizeY/2:sizeY/2]; mat = exp(-0.5*( ((X-meanX)/sigmaX).*((X-meanX)/sigmaX)... +((Y-meanY)/sigmaY).*((Y-meanY)/sigmaY)))... /((sigmaX*sigmaY)^(0.5)*pi); if cut > 0 maximun = max(max(mat))*cut; I = find(mat < maximun); mat(I) = 0; end; return;