matlabsurf图像拼接算法

以下是使用SURF算法实现图像配准和拼接的Matlab代码示例：

% 读取图像
img1 = imread('image1.jpg');
img2 = imread('image2.jpg');

% 提取SURF特征点
points1 = detectSURFFeatures(rgb2gray(img1));
points2 = detectSURFFeatures(rgb2gray(img2));

% 提取SURF特征描述符
[features1, valid_points1] = extractFeatures(rgb2gray(img1), points1);
[features2, valid_points2] = extractFeatures(rgb2gray(img2), points2);

% 进行特征匹配
indexPairs = matchFeatures(features1, features2);

% 选取匹配点对
matchedPoints1 = valid_points1(indexPairs(:, 1));
matchedPoints2 = valid_points2(indexPairs(:, 2));

% 估计变换矩阵
[tform, inlierPoints1, inlierPoints2] = estimateGeometricTransform(matchedPoints1, matchedPoints2, 'affine');

% 进行图像拼接
outputView = imref2d(size(img1));
panorama = imwarp(img2, tform, 'OutputView', outputView);
panorama = max(img1, panorama);

% 显示结果
figure;
imshow(panorama);

该代码首先读取两张待拼接的图像，然后使用SURF算法提取图像的特征点和特征描述符，并进行特征匹配。接着，使用估计的变换矩阵对第二张图像进行变换，最后将两张图像拼接在一起并显示结果。