这是一些评价和分类方法，用于遥感数据.rar_一些分类与评价方法_用于遥感数据与图像_评价_遥感分类方法_遥感数据分类

function [RGB nir]=svt_fuse(mul, pan) mul=uint8(mul); R=mul(:,:,1); G=mul(:,:,2); B=mul(:,:,3); Nir=mul(:,:,4); pR=histeq(pan,imhist(R)); pG=histeq(pan,imhist(G)); pB=histeq(pan,imhist(B)); pN=histeq(pan,imhist(Nir)); R=double(R); G=double(G); B=double(B); Nir=double(Nir); pR=double(pR); pG=double(pG); pB=double(pB); pN=double(pN); [M, N]=size(pan); R=imresize(R,[M, N],'bilinear'); G=imresize(G,[M, N],'bilinear'); B=imresize(B,[M, N],'bilinear'); Nir=imresize(Nir,[M, N],'bilinear'); hR = fuse_usvt(R,pR,2,[3,3], 1,2); hG = fuse_usvt(G,pG,2,[3,3], 1,2); hB = fuse_usvt(B,pB,2,[3,3], 1,2); hNir = fuse_usvt(Nir,pN,2,[3,3], 1,2); RGB=cat(3,hR,hG,hB); RGB=uint8(RGB); nir=uint8(hNir); function [M] = fuse_usvt(M1,M2,zt,ap,mp,mt); switch mt case 1 %atrous wavelet f1=[1/256 1/64 3/128 1/64 1/256;1/64 1/16 3/32 1/16 1/64;3/128 3/32 9/64 3/32 3/128;1/64 1/16 3/32 1/16 1/64;1/256 1/64 3/128 1/64 1/256]; for j=1:zt f2=fexp(f1,j-1); M1B = imfilter(M1,f2,'replicate'); M1S{j}=M1-M1B;M1=M1B; M2B = imfilter(M2,f2,'replicate'); M2S{j}=M2-M2B;M2=M2B; % MS{j} = selsv(M1S{j},M2S{j}, ap); % MS{j} = M2S{j}; a=M1S{j};b=M2S{j}; a(abs(b)>abs(a))=b(abs(b)>abs(a)); MS{j} = a; end case 2 %support value transfrom %gama=1,sig2=0.6,n=2,step=1 f1=[ -0.0158 -0.0136 -0.0102 -0.0136 -0.0158;... -0.0136 -0.0130 -0.0602 -0.0130 -0.0136; ... -0.0102 -0.0602 0.5051 -0.0602 -0.0102; ... -0.0136 -0.0130 -0.0602 -0.0130 -0.0136;... -0.0158 -0.0136 -0.0102 -0.0136 -0.0158]; j=1; gama=1;sig2=0.6*2^j;n=2^j;p1=1;p2=0;step=1;[AXK,XK,XK1,XK2,XK1T,XK2T,XK11T,XK22T,XK12T,XKKT,B] = ikernel(n,p1,p2,sig2,gama,step);l=2*n+1;l=l^2; OPK=AXK(round(l/2),:);f1=reshape(OPK,2*n+1,2*n+1); %support value transfrom for j=1:zt f2=fexp(f1,j-1); M1S{j} = imfilter(M1,f2,'replicate'); M1=M1-M1S{j}; M2S{j} = imfilter(M2,f2,'replicate'); M2=M2-M2S{j}; % MS{j} = selsv(M1S{j},M2S{j}, ap); MS{j} = M2S{j}; end end M=selbias(M1, M2, mp); for j=1:zt M=M+MS{j}; end %figure;imshow(M); return function [f3]=fexp(f1,s) [m n]=size(f1); zr=repmat(0,1,m); f2(1,:)=f1(1,:); j=1; for i=2:m for k=1:s,j=j+1; f2(j,:)=zr;end j=j+1;f2(j,:)=f1(i,:); end [z m]=size(f2); zr=repmat(0,z,1); f3(:,1)=f2(:,1); j=1; for i=2:m for k=1:s,j=j+1; f3(:,j)=zr;end j=j+1;f3(:,j)=f2(:,i); end return function Y = selsv(M1, M2, ap) %Y = selc(M1, M2, ap) coefficinet selection for highpass components % % M1 - coefficients A % M2 - coefficients B % mp - switch for selection type % mp == 1: choose max(abs) % mp == 2: salience / match measure with threshold == .75 (as proposed by Burt et al) % mp == 3: choose max with consistency check (as proposed by Li et al) % mp == 4: simple choose max % % Y - combined coefficients % (Oliver Rockinger 16.08.99) % check inputs [z1 s1] = size(M1); [z2 s2] = size(M2); if (z1 ~= z2) | (s1 ~= s2) error('Input images are not of same size'); end; % switch to method switch(ap(1)) case 1, % choose max(abs) mm = (abs(M1)) > (abs(M2)); Y = (mm.*M1) + ((~mm).*M2); case 2, % Burts method um = ap(2); th = .75; % compute salience S1 = conv2(es2(M1.*M1, floor(um/2)), ones(um), 'valid'); S2 = conv2(es2(M2.*M2, floor(um/2)), ones(um), 'valid'); % compute match MA = conv2(es2(M1.*M2, floor(um/2)), ones(um), 'valid'); MA = 2 * MA ./ (S1 + S2 + eps); % selection m1 = MA > th; m2 = S1 > S2; w1 = (0.5 - 0.5*(1-MA) / (1-th)); Y = (~m1) .* ((m2.*M1) + ((~m2).*M2)); Y = Y + (m1 .* ((m2.*M1.*(1-w1))+((m2).*M2.*w1) + ((~m2).*M2.*(1-w1))+((~m2).*M1.*w1))); case 3, % Lis method um = ap(2); % first step A1 = ordfilt2(abs(es2(M1, floor(um/2))), um*um, ones(um)); A2 = ordfilt2(abs(es2(M2, floor(um/2))), um*um, ones(um)); % second step mm = (conv2((A1 > A2).*1.0, ones(um), 'valid')) > floor(um*um/2); Y = (mm.*M1) + ((~mm).*M2); case 4, % simple choose max mm = M1 > M2; Y = (mm.*M1) + ((~mm).*M2); otherwise, error('unkown option'); end; return function Y = selbias(M1, M2, mp) %Y = selb(M1, M2, mp) coefficient selection for base image % % M1 - coefficients A % M2 - coefficients B % mp - switch for selection type % mp == 1: select A % mp == 2: select B % mp == 3: average A and B % % Y - combined coefficients % (Oliver Rockinger 16.08.99) switch (mp) case 1, Y = M1; case 2, Y = M2; case 3, Y = (M1 + M2)./2; case 4, % choose max(abs) mm = (abs(M1)) > (abs(M2)); Y = (mm.*M1) + ((~mm).*M2); case 5, % choose max(abs) mm = (abs(M1)) < (abs(M2)); Y = (mm.*M1) + ((~mm).*M2); otherwise, error('unknown option'); end; return function [AXK,XK,XK1,XK2,XK1T,XK2T,XK11T,XK22T,XK12T,XKKT,B] = ikernel(n,p1,p2,sig2,gama,step) %step=2; st=step;sm=1; N=(2*n+1)^2; Y=[1:1:N]'; cat=1; for i=-n*step:step:n*step for j=-n*step:step:n*step X(cat,:)=[i,j]; V(cat,1)=1*exp(-(i.^2+j.^2)/2); % if i==j,V(cat,1)=1*exp(-(i.^2+j.^2)/1);else V(cat,1)=0.0001;end cat=cat+1; end end for i=1:1:N for j=1:1:N % K(i,j)=exp(-((X(i,:)-X(j,:))*(X(i,:)-X(j,:))')/sig2); K(i,j)=p2*((X(i,:)*X(j,:)' + 1)^p1)+(1-p2)*( exp(-((X(i,:)-X(j,:))*(X(i,:)-X(j,:))')/sig2) ); % x=-((X(i,:)-X(j,:))*(X(i,:)-X(j,:))')/sig2;K(i,j)=1+x+x.^2./2+x.^3./6+x.^4./24+x.^5./120+x.^6./720; if i==j;K(i,j)=K(i,j)+gama;end % if i==j;K(i,j)=K(i,j)+gama./V(i,1);end % K(i,j)=mapkernel(ker,X(i,:),X(j,:),p1,p2); end end A=inv(K);%K1=reshape(K(round(N/2)+1,:),2*n+1,2*n+1);freqz2(K1); B=(ones(N,1))'*A/((ones(N,1))'*A*ones(N,1)); b=B*Y; alpha=A*(Y-b*ones(N,1)); c=1; for i=-n*step:step:n*step for j=-n*step:step:n*step XX(c,:)=[i,j]; c=c+1; end end c=1; for i=-n*step:step:n*step for j=-n*step:step:n*step for k=1:1:N XK(c,k)=p2*((XX(c,:)*X(k,:)' + 1)^p1)+ (1-p2)*( exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2) ); XK11(c,k)=p2*(p1*(p1-1)*X(k,1)^2*(XX(c,:)*X(k,:)' + 1)^(p1-2))+(1-p2)*(-2/sig2*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2)+4/sig2^2*(XX(c,1)-X(k,1))^2*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2)); XK12(c,k)=p2*(p1*X(k,1)*(p1-1)*X(k,2)*(XX(c,:)*X(k,:)' + 1)^(p1-2))+(1-p2)*( 4/sig2^2*(XX(c,1)-X(k,1))*(XX(c,2)-X(k,2))*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2) ); XK22(c,k)=p2*(p1*(p1-1)*X(k,2)^2*(XX(c,:)*X(k,:)' + 1)^(p1-2) )+(1-p2) * (-2/sig2*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2)+4/sig2^2*(XX(c,2)-X(k,2))^2*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2) ); XK1(c,k)=p2*(p1*X(k,1)*(XX(c,:)*X(k,:)' + 1)^(p1-1)) + (1-p2)*( -2/sig2*(XX(c,1)-X(k,1))*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2) ); XK2(c,k)=p2*(p1*X(k,2)*(XX(c,:)*X(k,:)' + 1)^(p1-1))+(1-p2)*( -2/sig2*(XX(c,2)-X(k,2))*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2) ); %XK13(c,k)=p2*(p1*(p1-1)*(p1-2)*X(k,1)^3*(XX(c,:)*X(k,:)' + 1)^(p1-3))+(1-p2)*(4/sig2^2*(XX(c,1)-X(k,1))*(3-2*(XX(c,1)-X(k,1))^2/sig2)*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2)); %XK23(c,k)=p2*(p1*(p1-1)*(p1-2)*X(k,2)^3*(XX(c,:)*X(k,:)' + 1)^(p1-3))+(1-p2)*(4/sig2^2*(XX(c,2)-X(k,2))*(3-2*(XX(c,2)-X(k,2))^2/sig2)*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2)); %XK121(c,k)=p2*(p1*(p1-1)*(p1-2)*X(k,1)^2*X(k,2)*(XX(c,:)*X(k,:)' + 1)^(p1-3))+(1-p2)*(4/sig2^2*(XX(c,2)-X(k,2))*(1-2*(XX(c,1)-X(k,1))^2/sig2)*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2) ); %XK212(c,k)=p2*(p1*(p1-1)*(p1-2)*X(k,1)*X(k,2)^2*(XX(c,:)*X(k,:)' + 1)^(p1-3))+(1-p2)*(4/sig2^2*(XX(c,1)-X(k,1))*(1-2*(XX(c,2)-X(k,2))^2/sig2)*exp(-(XX(c,:)-X(k,:))*(XX(c,:)-X(k,:))'/sig2) ); end c=c+1; end end xk=XK11+XK12;l=2*n+