Local Feature Detection and Extraction
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Local Feature Detection and Extraction
%Display two images.original = imread('cameraman.tif');figure;imshow(original);%The second image, is the original image rotated and scaled.scale = 1.3;J = imresize(original,scale);theta = 31;distorted = imrotate(J,theta);%旋转figureimshow(distorted);%Detecting the matching SURF features is the first step in determining the transform needed to correct the distorted image.ptsOriginal = detectSURFFeatures(original);ptsDistorted = detectSURFFeatures(distorted);%The detection step found several roughly corresponding blob structures in both images. Compare the detected blob features. %This process is facilitated by feature extraction, which determines a local patch descriptor[featuresOriginal,validPtsOriginal] = ... extractFeatures(original,ptsOriginal);[featuresDistorted,validPtsDistorted] = ... extractFeatures(distorted,ptsDistorted);%Find candidate matches.indexPairs = matchFeatures(featuresOriginal,featuresDistorted);%Find point locations from both images.matchedOriginal = validPtsOriginal(indexPairs(:,1));matchedDistorted = validPtsDistorted(indexPairs(:,2));%Display the candidate matches.figureshowMatchedFeatures(original,distorted,matchedOriginal,matchedDistorted)title('Candidate matched points (including outliers)');%Analyze the feature locations.[tform, inlierDistorted,inlierOriginal] = ... estimateGeometricTransform(matchedDistorted,... matchedOriginal,'similarity');%Display the matching points.figureshowMatchedFeatures(original,distorted,inlierOriginal,inlierDistorted)title('Matching points (inliers only)')legend('ptsOriginal','ptsDistorted')%Apply the computed geometric transform to the distorted image.outputView = imref2d(size(original));recovered = imwarp(distorted,tform,'OutputView',outputView);%Display the recovered image and the original image.figureimshowpair(original,recovered,'montage')
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