matlab多幅图像匹配代码
时间: 2023-07-09 15:36:39 浏览: 54
以下是一个基于SURF算法的多幅图像匹配的MATLAB代码示例:
```matlab
% 读取需要匹配的图像
img1 = imread('image1.jpg');
img2 = imread('image2.jpg');
img3 = imread('image3.jpg');
% 运行SURF算法,提取特征点和描述子
points1 = detectSURFFeatures(img1);
points2 = detectSURFFeatures(img2);
points3 = detectSURFFeatures(img3);
[features1, valid_points1] = extractFeatures(img1, points1);
[features2, valid_points2] = extractFeatures(img2, points2);
[features3, valid_points3] = extractFeatures(img3, points3);
% 对特征描述子进行匹配
indexPairs1 = matchFeatures(features1, features2);
indexPairs2 = matchFeatures(features2, features3);
% 使用RANSAC算法去除错误匹配点
matchedPoints1 = valid_points1(indexPairs1(:, 1));
matchedPoints2 = valid_points2(indexPairs1(:, 2));
[tform1, inlierPoints1, inlierPoints2] = estimateGeometricTransform(matchedPoints1, matchedPoints2, 'affine');
matchedPoints2 = valid_points2(indexPairs2(:, 1));
matchedPoints3 = valid_points3(indexPairs2(:, 2));
[tform2, inlierPoints2, inlierPoints3] = estimateGeometricTransform(matchedPoints2, matchedPoints3, 'affine');
% 应用变换矩阵,得到在同一坐标系下的所有图像
outputView = imref2d(size(img1));
panorama1 = imwarp(img1, tform1, 'OutputView', outputView);
panorama2 = imwarp(img2, tform1 * tform2, 'OutputView', outputView);
panorama3 = imwarp(img3, tform2, 'OutputView', outputView);
% 显示拼接后的图像
panorama = max(cat(4, panorama1, panorama2, panorama3), [], 4);
imshow(panorama);
```
这段代码假设图像已经对齐,然后通过SURF算法提取特征点和描述子,并使用matchFeatures函数进行匹配。然后使用RANSAC算法去除错误匹配点,并通过estimateGeometricTransform函数计算变换矩阵。最后使用imwarp函数应用变换矩阵,得到在同一坐标系下的所有图像,最后使用max函数将多幅图像拼接在一起。