SAR图像杂波统计建模

%%SAR 图像处理---参数统计模型 %reference--课件 %author:huangzhijian %2010-5-7 I = imread('E:\博士作业\SAR图像处理\灌木1.jpg'); %直方图统计 [row,col]=size(I(:,:,1)); data = zeros(row*col,1); for i=1:row for j=1:col data(j+(i-1)*col) = double (I(i,j,1))+0.00001; %避免出现像素值为0的情况 end end X = 0:1:255; histPdf=histc(data,X)/(row*col); %只使用R通道的分量进行统计 histPdf = histPdf'; histCdf = cumsum(histPdf); plot(X,histPdf,'-cp','MarkerSize',2); axis([0 150 0 0.03]); hold on; % plot(X,histCdf,'-rp','MarkerSize',2); % %选用Rayleigh为统计模型，进行参数估计 varRayl = raylfit(data); raylPdf = raylpdf(X,varRayl); raylCdf = raylcdf(X,varRayl); plot(X,raylPdf,'--ro','MarkerSize',2); hold on; %选用weibull分布为统计模型，进行参数估计 parmhat = wblfit(data); wblPdf = wblpdf(X,parmhat(1),parmhat(2)); wblCdf = wblcdf(X,parmhat(1),parmhat(2)); plot(X,wblPdf,'--g*','MarkerSize',2); hold on; %选用gamma分布为统计模型，进行参数估计 parmGam = gamfit(data); gamPDF = gampdf(X,parmGam(1),parmGam(2)); gamCdf = gamcdf(X,parmGam(1),parmGam(2)); plot(X,gamPDF,'--bs','MarkerSize',2);hold on; %选用log normal分布为统计模型，进行参数估计 parmLogn = lognfit(data); lognPDF = lognpdf(X,parmLogn(1),parmLogn(2)); lognCdf = logncdf(X,parmLogn(1),parmLogn(2)); plot(X,lognPDF,':md','MarkerSize',2); h = legend('直方图','rayl','weibul','gama','lognorm',5); set(h,'Interpreter','none'); %ks准则 %两个CDF幅值差的上确界，该值越小说明拟合程度越好 pR = max(abs(minus(histCdf,raylCdf))); pW = max(abs(minus(histCdf,wblCdf))); pG = max(abs(minus(histCdf,gamCdf))); pL = max(abs(minus(histCdf,lognCdf))); ksk = [pR,pW,pG,pL]; %chi-squre准则 %两PDF幅值的差方和，并与取相对值，该值越小说明拟合程度越好 PR = chi2test(histPdf,raylPdf); PW = chi2test(histPdf,wblPdf); PG = chi2test(histPdf,gamPDF); PL = chi2test(histPdf,lognPDF); chiP = [PR,PW,PG,PL]; %绝对值误差检验准则 absRayl = sum(abs(histPdf-raylPdf)); abswbl = sum(abs(histPdf-wblPdf)); absgama = sum(abs(histPdf-gamPDF)); abslogn = sum(abs(histPdf-lognPDF)); absR = [absRayl,abswbl,absgama,abslogn]; %偏度系数 %期望的偏离程度，自己定义 exHist=EX(histPdf); skwR = [abs(EX(raylPdf)-exHist),abs(EX(wblPdf)-exHist),abs(EX(gamPDF)-exHist),abs(EX(lognPDF)-exHist)]; %峰度系数 kurtosisR = [kurtosis(raylPdf),kurtosis(wblPdf),kurtosis(gamPDF),kurtosis(lognPDF)]; figure ; Xcor = 1:4; plot(Xcor,ksk,'-ro'); hold on; plot(Xcor,chiP,'--bs'); hold on; plot(Xcor,absR,'-.g*'); hold on; plot(Xcor,skwR,':rd'); hold on; plot(Xcor,kurtosisR,'-.cd'); hold on; axis([1 4 -0.1 1]); state = {'rayl','','weibul','','gama','','lognorm'}; set(gca,'xticklabel',state,'FontSize',12); h = legend('K-S','chi-square','ABS','偏度','gh',5); set(h,'Interpreter','none'); result=[varRayl,parmhat(1),parmhat(2),parmGam(1),parmGam(2),parmLogn(1),parmLogn(2)];