图像配准，图像拼接.rar

% load input images I1 = double(imread('left.jpg')); [h1 w1 d1] = size(I1); I2 = double(imread('right.jpg')); [h2 w2 d2] = size(I2); % show input images and prompt for correspondences figure; subplot(1,2,1); image(I1/255); axis image; hold on; title('first input image'); [X1 Y1] = ginput2(2); % get two points from the user subplot(1,2,2); image(I2/255); axis image; hold on; title('second input image'); [X2 Y2] = ginput2(2); % get two points from the user % estimate parameter vector (t) Z = [ X2' Y2' ; Y2' -X2' ; 1 1 0 0 ; 0 0 1 1 ]'; xp = [ X1 ; Y1 ]; t = Z \ xp; % solve the linear system a = t(1); % = s cos(alpha) b = t(2); % = s sin(alpha) tx = t(3); ty = t(4); % construct transformation matrix (T) T = [a b tx ; -b a ty ; 0 0 1]; % warp incoming corners to determine the size of the output image (in to out) cp = T*[ 1 1 w2 w2 ; 1 h2 1 h2 ; 1 1 1 1 ]; Xpr = min( [ cp(1,:) 0 ] ) : max( [cp(1,:) w1] ); % min x : max x Ypr = min( [ cp(2,:) 0 ] ) : max( [cp(2,:) h1] ); % min y : max y [Xp,Yp] = ndgrid(Xpr,Ypr); [wp hp] = size(Xp); % = size(Yp) % do backwards transform (from out to in) X = T \ [ Xp(:) Yp(:) ones(wp*hp,1) ]'; % warp % re-sample pixel values with bilinear interpolation clear Ip; xI = reshape( X(1,:),wp,hp)'; yI = reshape( X(2,:),wp,hp)'; Ip(:,:,1) = interp2(I2(:,:,1), xI, yI, '*bilinear'); % red Ip(:,:,2) = interp2(I2(:,:,2), xI, yI, '*bilinear'); % green Ip(:,:,3) = interp2(I2(:,:,3), xI, yI, '*bilinear'); % blue % offset and copy original image into the warped image offset = -round( [ min( [ cp(1,:) 0 ] ) min( [ cp(2,:) 0 ] ) ] ); Ip(1+offset(2):h1+offset(2),1+offset(1):w1+offset(1),:) = double(I1(1:h1,1:w1,:)); % show the result figure; image(Ip/255); axis image; title('mosaic image');