matlab——图像配准

只介绍两种方法：

第一种为手动选关键点：

function on2 = registerImages1(MOVING,FIXED,type)
    cpselect(FIXED, MOVING)   %选择关键点
    flag = input('Hit the Enter key after you finished control points selection');    
    mytform = cp2tform(input_points,base_points, 'projective');%求出投影变化的矩阵
    registered = imtransform(MOVING, mytform, 'bicubic');%进行变化
    on2=registered;%输出变换结果
end

第二种为image process toolbox中的自动feature-based 函数中的SURF 函数：

function on2 = registerImages1(MOVING,FIXED,type)
% This function can be used to image registration
% moving is image A, fixed is image B, 
% type is the method used
% type 'no'do not use image registration 
% type 'auto' use the automatic image registration.
% type 'user' use the user defined control points to registration
 

        %registerImages  Register grayscale images using auto-generated code from Registration Estimator app.
        %  [MOVINGREG] = registerImages(MOVING,FIXED) Register grayscale images
        %  MOVING and FIXED using auto-generated code from the Registration
        %  Estimator App. The values for all registration parameters were set
        %  interactively in the App and result in the registered image stored in the


        %-----------------------------------------------------------


        % Feature-based techniques require license to Computer Vision System Toolbox
        checkLicense()

        % Default spatial referencing objects
        fixedRefObj = imref2d(size(FIXED));
        movingRefObj = imref2d(size(MOVING));

        % Detect SURF features
        fixedPoints = detectSURFFeatures(FIXED,'MetricThreshold',750.000000,'NumOctaves',3,'NumScaleLevels',5);
        movingPoints = detectSURFFeatures(MOVING,'MetricThreshold',750.000000,'NumOctaves',3,'NumScaleLevels',5);

        % Extract features
        [fixedFeatures,fixedValidPoints] = extractFeatures(FIXED,fixedPoints,'Upright',false);
        [movingFeatures,movingValidPoints] = extractFeatures(MOVING,movingPoints,'Upright',false);

        % Match features
        indexPairs = matchFeatures(fixedFeatures,movingFeatures,'MatchThreshold',50.000000,'MaxRatio',0.500000);
        fixedMatchedPoints = fixedValidPoints(indexPairs(:,1));
        movingMatchedPoints = movingValidPoints(indexPairs(:,2));
        MOVINGREG.FixedMatchedFeatures = fixedMatchedPoints;
        MOVINGREG.MovingMatchedFeatures = movingMatchedPoints;

        % Apply transformation - Results may not be identical between runs because of the randomized nature of the algorithm
        tform = estimateGeometricTransform(movingMatchedPoints,fixedMatchedPoints,'projective');
        MOVINGREG.Transformation = tform;
        MOVINGREG.RegisteredImage = imwarp(MOVING, movingRefObj, tform, 'OutputView', fixedRefObj, 'SmoothEdges', true);

        on2=MOVINGREG.RegisteredImage;
end

function checkLicense()

% Check for license to Computer Vision System Toolbox
CVSTStatus = license('test','video_and_image_blockset');
if ~CVSTStatus
    error(message('images:imageRegistration:CVSTRequired'));
end

end

 

第二种其实就是工具箱函数的输出，如果需要使用，直接用工具箱就好。