lmd.zip_LMD函数_lmd特征_傅里叶特征_图像LMD_图像直方图

function [h]= lmd(im,winSize,patchSize,bins) % a=imread('D:\face.jpg'); % im=rgb2gray(a); % winSize=7; % bins=16; % patchSize=[4,4]; load(strcat('lmd_winSize',num2str(winSize),'_',num2str(bins),'bins.mat')); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% im = double(im); im = padarray(im,[floor(winSize/2),floor(winSize/2)],'symmetric','both'); %padarray的目的是扩展图像尺寸，因为要做卷积 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% initialize parameters r=(winSize-1)/2; x=-r:r; %% Form 1-D filters STFTalpha=1/winSize; % alpha in STFT approaches sigmaS=(winSize-1)/4; % Sigma for STFT Gaussian window % Basic STFT filters w0=(x*0+1); w1=exp(complex(0,-2*pi*x*STFTalpha)); w2=conj(w1); % Gaussian window gs=exp(-0.5*(x./sigmaS).^2)./(sqrt(2*pi).*sigmaS); % Windowed filters w0=gs.*w0; w1=gs.*w1; w2=gs.*w2; % Normalize to zero mean w1=w1-mean(w1); w2=w2-mean(w2); %12~33 在设置STFT的窗口 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% convmode='valid';%设置卷积模式，help covn2了解相关问题 %% 通过两次一维卷积实现四个频率的STFT Qa=conv2(conv2(im,w0.',convmode),w1,convmode);% 频率u1的STFT,其中，wo.'表示非共轭转置 Qb=conv2(conv2(im,w1.',convmode),w0,convmode);% 频率u2的STFT Qc=conv2(conv2(im,w1.',convmode),w1,convmode);% 频率u3的STFT Qd=conv2(conv2(im,w1.',convmode),w2,convmode);% 频率u4的STFT %38~41这四行是通过卷积运算实现了STFT，至于为什么STFT可通过卷积实现，可参看我发给你的文章及其参考文献5，6，11 %% 求不同频率STFT的幅度 Ma=abs(Qa); Mb=abs(Qb); Mc=abs(Qc); Md=abs(Qd); clear Qa Qb Qc Qd; %用abs命令求出幅值 %% LMD：Local Magnitude Descriptor ww = [1,2,4,8,16,32,64,128]; % 频率u1 LMD_u1=zeros(size(Ma,1)-2,size(Ma,2)-2); for ii=2:size(Ma,1)-1 for jj=2:size(Ma,2)-1 tmp=Ma(ii,jj); LMD_u1(ii-1,jj-1)=(tmp<=Ma(ii-1,jj-1))+(tmp<=Ma(ii-1,jj))*ww(2)+(tmp<=Ma(ii-1,jj+1))*ww(3)+(tmp<=Ma(ii,jj+1))*ww(4) ... +(tmp<=Ma(ii+1,jj+1))*ww(5)+(tmp<=Ma(ii+1,jj))*ww(6)+(tmp<=Ma(ii+1,jj-1))*ww(7)+(tmp<=Ma(ii,jj-1))*ww(8); end end % 频率u2 LMD_u2=zeros(size(Mb,1)-2,size(Mb,2)-2); for ii=2:size(Mb,1)-1 for jj=2:size(Mb,2)-1 tmp=Mb(ii,jj); LMD_u2(ii-1,jj-1)=(tmp<=Mb(ii-1,jj-1))+(tmp<=Mb(ii-1,jj))*ww(2)+(tmp<=Mb(ii-1,jj+1))*ww(3)+(tmp<=Mb(ii,jj+1))*ww(4) ... +(tmp<=Mb(ii+1,jj+1))*ww(5)+(tmp<=Mb(ii+1,jj))*ww(6)+(tmp<=Mb(ii+1,jj-1))*ww(7)+(tmp<=Mb(ii,jj-1))*ww(8); end end % 频率u3 LMD_u3=zeros(size(Mc,1)-2,size(Mc,2)-2); for ii=2:size(Mc,1)-1 for jj=2:size(Mc,2)-1 tmp=Mc(ii,jj); LMD_u3(ii-1,jj-1)=(tmp<=Mc(ii-1,jj-1))+(tmp<=Mc(ii-1,jj))*ww(2)+(tmp<=Mc(ii-1,jj+1))*ww(3)+(tmp<=Mc(ii,jj+1))*ww(4) ... +(tmp<=Mc(ii+1,jj+1))*ww(5)+(tmp<=Mc(ii+1,jj))*ww(6)+(tmp<=Mc(ii+1,jj-1))*ww(7)+(tmp<=Mc(ii,jj-1))*ww(8); end end % 频率u4 LMD_u4=zeros(size(Md,1)-2,size(Md,2)-2); for ii=2:size(Md,1)-1 for jj=2:size(Md,2)-1 tmp=Md(ii,jj); LMD_u4(ii-1,jj-1)=(tmp<=Md(ii-1,jj-1))+(tmp<=Md(ii-1,jj))*ww(2)+(tmp<=Md(ii-1,jj+1))*ww(3)+(tmp<=Md(ii,jj+1))*ww(4) ... +(tmp<=Md(ii+1,jj+1))*ww(5)+(tmp<=Md(ii+1,jj))*ww(6)+(tmp<=Md(ii+1,jj-1))*ww(7)+(tmp<=Md(ii,jj-1))*ww(8); end end %%%%以LBP方式从4个幅值图中提取LBP描述子 %% uniform pattern of histogram clear Ma Mb Mc Md; LMD=struct; LMD(1).u=LMD_u1;LMD(2).u=LMD_u2;LMD(3).u=LMD_u3;LMD(4).u=LMD_u4;% lmdhist1=[]; for ii=1:length(LMD) tmp_LMD = imPart(LMD(ii).u,patchSize);% for jj=1:numel(tmp_LMD) tmp=hist(tmp_LMD{jj}(:),0:255); histgram=tmp/sum(tmp); tmp=tmp/sum(tmp); [histgram]=scale_bins(tmp,hist_idx_mag,bins); lmdhist1=[lmdhist1,histgram]; end end h=lmdhist1'; % 使用直方图信息，各个频率串接使用 %97~111行在压缩直方图