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matlab 批量处理梯形变形

matlab 批量处理梯形变形

作者: Kerwin_H | 来源:发表于2019-06-20 15:43 被阅读0次

    file_path = 'F:\\test\';% 图像文件夹路径

    img_path_list = dir(strcat(file_path,'*.png'));%获取该文件夹中所有.jpg格式的图像

    img_num = length(img_path_list);%获取图像总数

    if img_num > 0 %有满足条件的图像

    for pn = 1:img_num %逐一读取图像

                image_name = img_path_list(pn).name;% 图像名

                img_origin =  imread(strcat(file_path,image_name));%读取图像

                fprintf('%d %s\n',pn,strcat(file_path,image_name));% 显示正在处理的图像名

                S = distortion002(imread(strcat(file_path,image_name)));

                imwrite(S,image_name);

    %%此处添加具体的图像处理程序

    end

    end

    function I = distortion002(Idistorted)

    %clear;

    A =[639  0  320.5; 

        0    399 200.5; 

        0    0  1]; 

    fx = A(1,1); 

    fy = A(2,2); 

    cx = A(1,3); 

    cy = A(2,3); 

    K = A; 

    %Idistorted = imread('4946978_left.png'); 

    %Idistorted = rgb2gray(Idistorted); 

    Idistorted = im2double(Idistorted); 

    I = zeros(size(Idistorted)); 

    [i ,j] = find(~isnan(I)); 

    % Xp = the xyz vals of points on the z plane 

    Xp = (K)\[j i ones(length(i),1)]'; 

    % Now we calculate how those points distort i.e forward map them through the distortion 

    %r2 = Xp(1,:).^2+Xp(2,:).^2; 

    x = Xp(1,:); 

    y = Xp(2,:); 

    theta = deg2rad(12.5);%X轴旋转角度

    focal = 446 ;  %相机内参,焦距

    Ph = 400 ;      %相机内参,画幅height

    alpha = atan(2*focal/Ph);

    beta = alpha - theta;

    h2 = sin(alpha)*Ph/sin(beta);

    deltaS = sin(theta)*Ph/sin(beta);

    S = (Ph/2)/cos(alpha);

    aa = (S+deltaS)/S;

    x1=zeros(400,1);

    for m=1:400

    x1(m,1)=(m-1)/399;

    end

    t=aa-1;

    for m=  1  :  400  %列1-21,x - →  竖线

    for n=  1  :  640    %hang 1-21,x + ←

    x(400*(n-1)+m)=x(400*(n-1)+m)/(1+t*x1(m)) ;

    end

    end

    bb=h2/Ph;

    y=y/bb;%y方向缩放

    %x = x.*(1+k1*r2 + k2*r2.^2 + k3*r2.^3) + 2*p1.*x.*y + p2*(r2 + 2*x.^2); 

    %y = y.*(1+k1*r2 + k2*r2.^2 + k3*r2.^3) + 2*p2.*x.*y + p1*(r2 + 2*y.^2); 

    % u and v are now the distorted cooridnates 

    u = reshape(fx*x + cx,size(I)); 

    v = reshape(fy*y + cy,size(I)); 

    % Now we perform a backward mapping in order to undistort the warped image coordinates 

    I = interp2(Idistorted, u, v); 

    subplot(121); imshow(Idistorted); 

    subplot(122); imshow(I);

    %imwrite(I,'I001.png');

    end

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