基于MATALB编程的微泡检测，基于MATALB编程的目标检测，图像处理（代码完整，数据齐全）

close all force; %% 读取图片，转化为灰度 z = double(rgb2gray(imread('111.jpg'))); % z = double((imread('mozart1.pgm'))); bb=downsample(z,10); cc=downsample(bb.',10); z=cc.'; clc s = size(z); %% 幅度归一化 z = z/max(max(z)); %% 计算z的imfilter，选中imfilter，按键F1，看注释 gradx = 0.5*imfilter(z,[-1 0 1]); grady = 0.5*imfilter(z,[-1 0 1]'); frac = 0.5; t = gradx; %% 屏蔽超过阈值的点 t(gradx<frac*max(max(gradx))) = 0; t2 = gradx; t2(gradx>frac*min(min(gradx))) = 0; %% 屏蔽低于阈值的点，底下的语句大部分很简单，应该可以看懂吧 t3 = grady; t3(grady<frac*max(max(grady))) = 0; t4 = grady; t4(grady>frac*min(min(grady))) = 0; gt = zeros(s); ft = zeros(s); ft(t~=0) = -2; ft(t2~=0) = 2; gt(t3~=0) = 2; gt(t4~=0) = -2; ft1 = ft; gt1 = gt; y = ft.^2 + gt.^2; ft1(y~=4) = 0; gt1(y~=4) = 0; ite = 5; %迭代次数 可以设置 lamb = 1; fs = ft1; gs = gt1; laplacian = (1/8)*[1 1 1; 1 0 1; 1 1 1]; %% 开始迭代，循环 for k = 1:ite %% 计算r1 r2 r1 = ((-1*(fs.^2))+(-1*(gs.^2))+4)./(((fs.^2))+((gs.^2))+4); r2 = 1./(((fs.^2))+((gs.^2))+4).^2; %% 计算频域的平滑函数 fsmooth = imfilter(fs,laplacian); fdata = (1/lamb)*32*fs.*r2.*(z-r1); % fs = fsmooth + fdata; fs(ft==0) = fsmooth(ft==0) - fdata(ft==0); gsmooth = imfilter(gs,laplacian); gdata = (1/lamb)*32*gs.*r2.*(z-r1); % gs = gsmooth + gdata; gs(gt==0) = gsmooth(gt==0) - gdata(gt==0); end %% 根据以上计算的fs和gs计算p和q，准备分别从p和q重建三维图像 p = (fs./2).*((1+r1)./r1); q = (gs./2).*((1+r1)./r1); %% 求pq模仿的倒数 r = 1./((p.^2 + q.^2 + 1).^2); % mesh(r1); p1 = p; q1 = q; p1(z==0) = 0; q1(z==0) = 0; ps=zeros(s); qs=zeros(s); %% 完成重建 for i= 1:s(2) ps(:,i) = sum(p1(:,1:i),2); end ps(z==0) = 0; for i = 1:s(1) qs(i,:)= sum(q1(i:end,:)); end qs(z==0) = 0; zs = ps+qs; %% 画图 figure;subplot(1,2,1),imshow(p,[]);title('p');subplot(1,2,2),imshow(q,[]);title('q');hold on; figure;subplot(1,2,1),imshow(fs,[]);title('f');subplot(1,2,2),imshow(gs,[]);title('g');hold on; figure;subplot(1,2,1),mesh(r1);title('3-D reconstructed from f&g');subplot(1,2,2),mesh(r);title('3-D reconstructed from p&q');hold on; %% figure; subplot(1,2,1); plot(p(:,150)); subplot(1,2,2) plot(p(100,:),'-r')