SAR.rar_SAR_sar 分解_sar 聚类_极化散射熵_熵 聚类

%% read Coherence matrix Raw data % Procedure % read_T.m (Here) -> save_C.m -> constr_Accu.m -> NL_for_Accu.m -> show_C.m %% clc; clear all; clear; clc;tic; close all; row =750 ; col =1024 ; data = zeros(row,col,9); filePath = 'C:\Documents and Settings\zhaojun\桌面\新建文件夹\T3\'; fIn = fopen([filePath 'T11.bin'],'r'); data(:,:,1) = fread(fIn,[col,row],'float').'; fclose(fIn); % SarPowerHisteq(data(:,:,1)); fIn = fopen([filePath 'T22.bin'],'r'); data(:,:,2) = fread(fIn,[col,row],'float').'; fclose(fIn); fIn = fopen([filePath 'T33.bin'],'r'); data(:,:,3) = fread(fIn,[col,row],'float').'; fclose(fIn); fIn = fopen([filePath 'T12_real.bin'],'r'); data(:,:,4) = fread(fIn,[col,row],'float').'; fclose(fIn); fIn = fopen([filePath 'T13_real.bin'],'r'); data(:,:,5) = fread(fIn,[col,row],'float').'; fclose(fIn); fIn = fopen([filePath 'T23_real.bin'],'r'); data(:,:,6) = fread(fIn,[col,row],'float').'; fclose(fIn); fIn = fopen([filePath 'T12_imag.bin'],'r'); data(:,:,7) = fread(fIn,[col,row],'float').'; fclose(fIn); fIn = fopen([filePath 'T13_imag.bin'],'r'); data(:,:,8) = fread(fIn,[col,row],'float').'; fclose(fIn); fIn = fopen([filePath 'T23_imag.bin'],'r'); data(:,:,9) = fread(fIn,[col,row],'float').'; fclose(fIn); clear fIn; z(:,:,1)=data(:,:,2); z(:,:,2)=data(:,:,3); z(:,:,3)=data(:,:,1); imshow(z*256); % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%求在源矩阵中的位置，对该位置的元素分类 % Span = data(:,:,1)+data(:,:,2)+data(:,:,3); % numbyspan=5; % everygroup=1024*750/numbyspan; % sspan=reshape(Span,768000,1); % %hist(sspan,300); % [BB,IX]=sort(sspan); % attribute=zeros(row,col,4); % for j=1:everygroup % m=ceil(IX(j)/1024); % n=IX(j)-1024*(m-1); % attribute(m,n,1)=1; % end % for j=everygroup+1:everygroup*2 % m=ceil(IX(j)/1024); % n=IX(j)-1024*(m-1); % attribute(m,n,1)=2; % end % for j=everygroup*2+1:everygroup*3 % m=ceil(IX(j)/1024); % n=IX(j)-1024*(m-1); % attribute(m,n,1)=3; % end % for j=everygroup*3+1:everygroup*4 % m=ceil(IX(j)/1024); % n=IX(j)-1024*(m-1); % attribute(m,n,1)=4; % end % for j=everygroup*4+1:everygroup*5 % m=ceil(IX(j)/1024); % n=IX(j)-1024*(m-1); % attribute(m,n,1)=5; % end % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%求在源矩阵中的位置，对该位置的元素分类 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%用Span聚类 % for n=1:5 % % class1=1; class2=2; class3=3; class4=4; class5=5; % [T1 ,num1] = f_covariance_matrix(data,attribute,1); % [T2 ,num2] = f_covariance_matrix(data,attribute,2); % [T3 ,num3] = f_covariance_matrix(data,attribute,3); % [T4 ,num4] = f_covariance_matrix(data,attribute,4); % [T5 ,num5] = f_covariance_matrix(data,attribute,5); % [attribute1]=f_classify_mlbyspan(data,T1,T2,T3,T4,T5); % attribute(:,:,1)=attribute1; % end % figure;imshow(attribute(:,:,1)); % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%用Span聚类 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%freeman分解 % [Ps,Pd,Pv] = fThreeDecomposition(data,1); % for m = 1:row % for n=1:col % if Ps(m,n)<=Pd(m,n) % if Pd(m,n)<=Pv(m,n) % attribute(m,n,2)=3; % else % attribute(m,n,2)=2; % end % else % if Ps(m,n)<=Pv(m,n) % attribute(m,n,2)=3; % else % attribute(m,n,2)=1; % end % end % end % end % mean2(Ps)%表面散射 1 蓝色 % mean2(Pd)%二次散射 2 红色 % mean2(Pv)%体散射 3 绿色 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%freeman分解 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%熵聚类 % %entropy=zeros(row,col);alpha=zeros(row,col); % [entropy,alpha,A] = f_myCalHAlphaSpan(data); % for m = 1:row % for n=1:col % if entropy(m,n)<=0.5 % attribute(m,n,3)=1;%低熵 % elseif entropy(m,n)>0.5&&entropy(m,n)<=0.9 % attribute(m,n,3)=2;%中熵 % else % attribute(m,n,3)=3;%高熵 % end % end % end % for m = 1:row % for n=1:col % if A(m,n)<=0.5 % attribute(m,n,4)=1;%低反熵 % else % attribute(m,n,4)=2;%高反熵 % end % end % end % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%用熵聚类 % for n=1:3 % [T111 ,num111] = f_covariance_matrix3(data,attribute,1,1,1); % [T112 ,num112] = f_covariance_matrix3(data,attribute,1,1,2); % [T113 ,num113] = f_covariance_matrix3(data,attribute,1,1,3); % [attribute3]=f_classify_mlbyH(data,T111,T112,T113,attribute,1,1); % for m = 1:row % for n=1:col % if attribute3(m,n)~=0 % attribute(m,n,3)=attribute3(m,n); % end % end % end % end % for n=1:3 % [T121 ,num121] = f_covariance_matrix3(data,attribute,1,2,1); % [T122 ,num122] = f_covariance_matrix3(data,attribute,1,2,2); % [T123 ,num123] = f_covariance_matrix3(data,attribute,1,2,3); % [attribute3]=f_classify_mlbyH(data,T121,T122,T123,attribute,1,2); % for m = 1:row % for n=1:col % if attribute3(m,n)~=0 % attribute(m,n,3)=attribute3(m,n); % end % end % end % end % for n=1:3 % [T131 ,num131] = f_covariance_matrix3(data,attribute,1,3,1); % [T132 ,num132] = f_covariance_matrix3(data,attribute,1,3,2); % [T133 ,num133] = f_covariance_matrix3(data,attribute,1,3,3); % [attribute3]=f_classify_mlbyH(data,T131,T132,T133,attribute,1,3); % for m = 1:row % for n=1:col % if attribute3(m,n)~=0 % attribute(m,n,3)=attribute3(m,n); % end % end % end % end % % for n=1:3 % [B111 ,num111] = f_covariance_matrix3(data,attribute,2,1,1); % [B112 ,num112] = f_covariance_matrix3(data,attribute,2,1,2); % [B113 ,num113] = f_covariance_matrix3(data,attribute,2,1,3); % [attribute3]=f_classify_mlbyH(data,B111,B112,B113,attribute,2,1); % for m = 1:row % for n=1:col % if attribute3(m,n)~=0 % attribute(m,n,3)=attribute3(m,n); % end % end % end % end % for n=1:3 % [B121 ,num121] = f_covariance_matrix3(data,attribute,2,2,1); % [B122 ,num122] = f_covariance_matrix3(data,attribute,2,2,2); % [B123 ,num123] = f_covariance_matrix3(data,attribute,2,2,3); % [attribute3]=f_classify_mlbyH(data,B121,B122,B123,attribute,2,2); % for m = 1:row % for n=1:col % if attribute3(m,n)~=0 % attribute(m,n,3)=attribute3(m,n); % end % end % end % end % for n=1:3 % [B131 ,num131] = f_covariance_matrix3(data,attribute,2,3,1); % [B132 ,num132] = f_covariance_matrix3(data,attribute,2,3,2); % [B133 ,num133] = f_covariance_matrix3(data,attribute,2,3,3); % [attribute3]=f_classify_mlbyH(data,B131,B132,B133,attribute,2,3); % for m = 1:row % for n=1:col % if attribute3(m,n)~=0 % attribute(m,n,3)=attribute3(m,n); % end % end % end % end % for n=1:3 % [C111 ,num111] = f_covariance_matrix3(data,attribute,3,1,1); % [C112 ,num112] = f_covariance_matrix3(data,attribute,3,1,2); % [C113 ,num113] = f_covariance_matrix3(data,attribute,3,1,3); % [attribute3]=f_classify_mlbyH(data,C111,C112,C113,attribute,3,1); % for m = 1:row % for n=1:col % if attribute3(m,n)~=0 % attribute(m,n,3)=attribute3(m,n); % end % end % end % end % for n=1:3 % [C121 ,num121] = f_covariance_matrix3(data,attribute,3,2,1); % [C122 ,num122] = f_covariance_matrix3(data,attribute,3,2,2); % [C123 ,num123] = f_covariance_matrix3(data,attribute,3,2,3); % [attribute3]=f_classify_mlbyH(data,C121,C122,C123,attribute,3,2); % for m = 1:row % for n=1:co