Suche Überlappungsbereich von zwei Bildern mit Matlab

Question

ich den Überlappungsbereich der beiden Bilder mit Matlab finden möchten.

Answer 1

Wenn es Ihr ultimatives Ziel ist, ein Panorama zu stitchen, sollten Sie vielleicht this code in Betracht ziehen.

Um den Überlappungsbereich zu erhalten, müssen Sie zuerst die Bilder registrieren (finden Sie heraus, WIE sie sich überlappen - oder eher mathematisch: Finden Sie die Transformation von Bild 1 zu Bild 2). Um dies zu tun, müssen Sie in beiden Bildern übereinstimmende Punkte finden.

Der folgende Code macht das für zwei Bilder (inspiriert von this code, die älteren MATLAB-Funktionen verwendet).

%% >>>>>>> load images and calculate their transformation <<<<<<< %% 
im1 = imread('1.png'); 
im2 = imread('2.png'); 
imshowpair(im1, im2, 'montage'); 

% calculate features on grayscale image 
im1g = rgb2gray(im1); 
im2g = rgb2gray(im2); 
points1 = detectSURFFeatures(im1g); 
[features1, points1] = extractFeatures(im1g, points1); 
points2 = detectSURFFeatures(im2g); 
[features2, points2] = extractFeatures(im2g, points2); 

% Find correspondences between im1 and im2 
indexPairs = matchFeatures(features1, features2, 'Unique', true); 
matchedPoints1 = points1(indexPairs(:,1), :); 
matchedPoints2 = points2(indexPairs(:,2), :); 

% Identity transformation 
transform_eye = projective2d(eye(3)); 
% Estimate the transformation between im1 and im2 
% we use a 'similarity' transform (translation/rotation), which treats the 
% images as rigid bodys. 'affine'/'projective' transformations allow for 
% warping the images itself (the overlap might not be a rectangle). 
transform = estimateGeometricTransform(matchedPoints1, matchedPoints2,... 
    'similarity', 'Confidence', 99.9, 'MaxNumTrials', 2000); 

%% >>>>>>> apply transformation to images <<<<<<< %% 

% create a world coordinate system (RF) that has space to store 
% the reference image (im1) and the transformed image (im2) 
R2 = imref2d(size(im2)); 
[~, R2T]=imwarp(im2,R2,transform); 
xLimits=[min(0.5,R2T.XWorldLimits(1)) max(size(im1,2), R2T.XWorldLimits(2))]; 
yLimits=[min(0.5,R2T.YWorldLimits(1)) max(size(im1,1), R2T.YWorldLimits(2))]; 
width = round(xLimits(2) - xLimits(1)); 
height = round(yLimits(2) - yLimits(1)); 
RF = imref2d([height width], xLimits, yLimits); 

% transform both images with regard to the world coordinate system RF 
im1t=imwarp(im1,transform_eye,'OutputView',RF); % im1 stays in place (identity transform) 
im2t=imwarp(im2,transform,'OutputView',RF); % im2 is transformed 

% visualize result 
imOverlay = im1t/2 + im2t/2; 
imshow(imOverlay); 

%% >>>>>>> get the overlap area only <<<<<<< %% 
% if you only want the overlap area, apply the transform to image masks 
im1bw = ones(size(im1)); % mask1 
im2bw = ones(size(im2)); % mask2 
im1bwt=imwarp(im1bw,transform_eye,'OutputView',RF); % im1 stays in place (identity transform) 
im2bwt=imwarp(im2bw,transform,'OutputView',RF); % im2 is transformed 

% visualize result 
maskOverlap = im1bwt + im2bwt - 1; 
imshow(maskOverlap); 
% maskOverlap is a bw image that contains 'true' for overlap pixels 
% you can use that for cropping imOverlay or 
% use bwarea or regionprops to calculate the area