基于小波包和支持向量机的红外图像检测和识别（含Matlab源码）

clc;clear; % close; tic f = imread('车辆与人/行人-09.jpeg'); % 行人识别 f = imread('00001/img_00009.bmp'); % 车辆识别 if ndims(f) > 2 % 查看维度 f = rgb2gray(f); % 转化成灰度图 end order = 4; % 小波包 % depth = 4; f = double(f); f = medfilt2(f); % 中值滤波器，消躁 T = wpdec2(f,order,'db16'); % db小波 % T = wpdec2(f,order,'dmey'); % meyer小波 % T = wpdec2(f,order,'coif1'); % T = wpdec2(f,order,'haar'); tt1 = wprcoef(T,[3 5]); tt2 = wprcoef(T,[3 10]); tt3 = wprcoef(T,[3 20]); tt4 = wprcoef(T,[3 50]); tt5 = wprcoef(T,[3 100]); tt6 = wprcoef(T,[3 200]); figure subplot(3,1,2) mesh(f) title('原图') % imagesc(uint8(tt1)); figure subplot(3,2,1) mesh(tt1);title('细节图1'); subplot(3,2,2) mesh(tt2);title('细节图2'); subplot(3,2,3) mesh(tt3);title('细节图3'); subplot(3,2,4) mesh(tt4);title('细节图4'); subplot(3,2,5) mesh(tt5);title('细节图5'); subplot(3,2,6) mesh(tt6);title('细节图6'); figure plot(T); % 绘制小波包树 d = tnodes(T); firstIndex = d(1); lastIndex = d(end); gaus = []; for i = firstIndex:lastIndex cfs = wpcoef(T,i); cfs = cfs*1.5; igass = judgeGausses(cfs); gaus = [gaus,igass]; if i == firstIndex cp = wpcoef(T,i); [h,w] = size(cp); y = zeros(h,w); T = write(T,'cfs',i,y); end if i > (firstIndex+lastIndex)/2 m = i; cp = wpcoef(T,m); [h,w] = size(cp); y = zeros(h,w); T = write(T,'cfs',m,y); end end plot(T);%绘制小波包树 f1 = wprec2(T); means = mean2(f1); stds = std2(f1); v = means + stds*4; % [l1,l2] = size(f1); for i = 1:l1 for j = 1:l2 if f1(i,j) < .1*v f1(i,j) = 0; % else % f1(i,j) = 1; end end end z = f1; a = max(max(z)); [m,n] = find(z == a); figure subplot(121) imagesc(f); title('原始红外图像'); colormap('gray') subplot(122) imagesc(uint8(f1)); % hold on % plot(n,m,'r*') title('小波变换背景抑制效果'); colormap('gray') figure imagesc(uint8(f1)); dest = drawRect( f, [n-25,m-25], [50,50]); imagesc(uint8(dest));