【图像分割】 FCM侧扫声呐图像分割【含Matlab源码 1478期】.zip

function dst = BEMD(src,a,b,c,d,e) % BEMD This program calculates the Bidimensional EMD of a 2-d signal using % the process of sifting. It is dependent on the function SIFT. % Assigning the initial values of 'h' (data for sifting) and 'k' (imf index) h_func = src; k=1; % The process of Sifting dst=zeros(size(h_func)); % figure,imshow(orig); while(k<5) [imf_temp, residue_temp] = sift(h_func); imf_matrix(:,:,k) = imf_temp; %#ok<AGROW> k = k+1; h_func = residue_temp;%余量图像 end % Assigning the final residue to the last IMF index imf_matrix(:,:,k) = residue_temp;%4个IMF图像和一个余量图像 % orig =orig-residue_temp; % orig =imf_matrix(:,:,1)+imf_matrix(:,:,2)+imf_matrix(:,:,3); dst =a*imf_matrix(:,:,1)+b*imf_matrix(:,:,2)+c*imf_matrix(:,:,3)+d*imf_matrix(:,:,4)+e*imf_matrix(:,:,5); % orig =orig+h_f; %imf_matrix(:,:,k+1)=orig; % End of BEMD Computation % subplot(3,2,1),imshow(cast(imf_matrix(:,:,1) ,'uint8')); % subplot(3,2,2),imshow(cast(imf_matrix(:,:,2) ,'uint8')); % subplot(3,2,3),imshow(cast(imf_matrix(:,:,3) ,'uint8')); % subplot(3,2,4),imshow(cast(imf_matrix(:,:,4) ,'uint8')); % subplot(3,2,5),imshow(cast(imf_matrix(:,:,5) ,'uint8')); % figure(2),imshow(cast(dst ,'uint8')); % figure,imshow(cast(imf_matrix(:,:,1) ,'int8')); % figure,imshow(cast(imf_matrix(:,:,2) ,'int8')); % figure,imshow(cast(imf_matrix(:,:,3) ,'int8')); % figure,imshow(cast(imf_matrix(:,:,4) ,'int8')); % figure,imshow(cast(imf_matrix(:,:,5) ,'int8')); % %subplot(3,2,4),imshow(imf_matrix(:,:,4)); % % subplot(3,2,5),imshow(imf_matrix(:,:,5)); % orig=cast(orig ,'int8'); %figure,imshow(im ); % figure,imshow(orig); end %% function [ h_imf residue ] = sift( input_image ) % This function sifts for a single IMF of the given 2D signal input % Pre-processing [len bre] = size(input_image); x = 1:len; y = 1:bre; input_image_temp = input_image; while(1) % Finding the extrema in the 2D signal [zmax imax zmin imin] = extrema2(input_image_temp); [xmax ymax] = ind2sub(size(input_image_temp),imax); [xmin ymin] = ind2sub(size(input_image_temp),imin); % Interpolating the extrema to get the extrema suraces [zmaxgrid , ~, ~] = gridfit(ymax,xmax,zmax,y,x); [zmingrid, ~, ~] = gridfit(ymin,xmin,zmin,y,x); % Averaging the extrema to get the Zavg surface zavggrid = (zmaxgrid + zmingrid)/2; % Computation of the h_imf (IMF for the 'h' input) h_imf = input_image_temp - zavggrid; % Computing IMF cost eps = 0.00000001; num = sum(sum((h_imf-input_image_temp).^2)); den = sum(sum((input_image_temp).^2)) + eps; cost = num/den; % Checking the IMF accuracy if cost<0.2 break; else input_image_temp = h_imf; end end % Computation of the Residue after IMF computation residue = input_image - h_imf; end %% function [xmax,imax,xmin,imin] = extrema(x) %EXTREMA Gets the global extrema points from a time series. % [XMAX,IMAX,XMIN,IMIN] = EXTREMA(X) returns the global minima and maxima % points of the vector X ignoring NaN's, where % XMAX - maxima points in descending order % IMAX - indexes of the XMAX % XMIN - minima points in descending order % IMIN - indexes of the XMIN % % DEFINITION (from http://en.wikipedia.org/wiki/Maxima_and_minima): % In mathematics, maxima and minima, also known as extrema, are points in % the domain of a function at which the function takes a largest value % (maximum) or smallest value (minimum), either within a given % neighbourhood (local extrema) or on the function domain in its entirety % (global extrema). % % Example: % x = 2*pi*linspace(-1,1); % y = cos(x) - 0.5 + 0.5*rand(size(x)); y(40:45) = 1.85; y(50:53)=NaN; % [ymax,imax,ymin,imin] = extrema(y); % plot(x,y,x(imax),ymax,'g.',x(imin),ymin,'r.') % % See also EXTREMA2, MAX, MIN % Written by % Lic. on Physics Carlos Adri醤 Vargas Aguilera % Physical Oceanography MS candidate % UNIVERSIDAD DE GUADALAJARA % Mexico, 2004 % % nubeobscura@hotmail.com % From : http://www.mathworks.com/matlabcentral/fileexchange % File ID : 12275 % Submited at: 2006-09-14 % 2006-11-11 : English translation from spanish. % 2006-11-17 : Accept NaN's. % 2007-04-09 : Change name to MAXIMA, and definition added. xmax = []; imax = []; xmin = []; imin = []; % Vector input? Nt = numel(x); if Nt ~= length(x) error('Entry must be a vector.') end % NaN's: inan = find(isnan(x)); indx = 1:Nt; if ~isempty(inan) indx(inan) = []; x(inan) = []; Nt = length(x); end % Difference between subsequent elements: dx = diff(x); % Is an horizontal line? if ~any(dx) return end % Flat peaks? Put the middle element: a = find(dx~=0); % Indexes where x changes lm = find(diff(a)~=1) + 1; % Indexes where a do not changes d = a(lm) - a(lm-1); % Number of elements in the flat peak a(lm) = a(lm) - floor(d/2); % Save middle elements a(end+1) = Nt; % Peaks? xa = x(a); % Serie without flat peaks b = (diff(xa) > 0); % 1 => positive slopes (minima begin) % 0 => negative slopes (maxima begin) xb = diff(b); % -1 => maxima indexes (but one) % +1 => minima indexes (but one) imax = find(xb == -1) + 1; % maxima indexes imin = find(xb == +1) + 1; % minima indexes imax = a(imax); imin = a(imin); nmaxi = length(imax); nmini = length(imin); % Maximum or minumim on a flat peak at the ends? if (nmaxi==0) && (nmini==0) if x(1) > x(Nt) xmax = x(1); imax = indx(1); xmin = x(Nt); imin = indx(Nt); elseif x(1) < x(Nt) xmax = x(Nt); imax = indx(Nt); xmin = x(1); imin = indx(1); end return end % Maximum or minumim at the ends? if (nmaxi==0) imax(1:2) = [1 Nt]; elseif (nmini==0) imin(1:2) = [1 Nt]; else if imax(1) < imin(1) imin(2:nmini+1) = imin; imin(1) = 1; else imax(2:nmaxi+1) = imax; imax(1) = 1; end if imax(end) > imin(end) imin(end+1) = Nt; else imax(end+1) = Nt; end end xmax = x(imax); xmin = x(imin); % NaN's: if ~isempty(inan) imax = indx(imax); imin = indx(imin); end % Same size as x: imax = reshape(imax,size(xmax)); imin = reshape(imin,size(xmin)); % Descending order: [~,inmax] = sort(-xmax); clear temp xmax = xmax(inmax); imax = imax(inmax); [xmin,inmin] = sort(xmin); imin = imin(inmin); end %% function [xymax,smax,xymin,smin] = extrema2(xy,varargin) %EXTREMA2 Gets the extrema points from a surface. % [XMAX,IMAX,XMIN,IMIN] = EXTREMA2(X) returns the maxima and minima % elements of the matriz X ignoring NaN's, where % XMAX - maxima points in descending order (the bigger first and so on) % IMAX - linear indexes of the XMAX % XMIN - minima points in descending order % IMIN - linear indexes of the XMIN. % The program uses EXTREMA. % % The extrema points are searched only through the column, the row and % the diagonals crossing each matrix element, so it is not a perfect % mathematical program and for this reason it has an optional argument. % The user should be aware of these limitations. % % [XMAX,IMAX,XMIN,IMIN] = EXTREMA2(X,1) does the same but without % searching through the diagonals (less strict and perhaps the user gets % more output points). % % DEFINITION (from http://en.wikipedia.org/wiki/Maxima_and_minima): % In mathematics, maxima and minima, also known as extrema, are points in % the domain of a function at which the function takes a largest value % (maximum) or smallest value (minimum), either within a given % neighbourhood (local extrema) or on the function domain in its entirety % (global extrema). % % Note: To change the linear index to (i,j) use IND2S