寻踪投影评价法MATLAB代码

以下是一份基于寻踪投影评价法的 MATLAB 代码，希望能对你有所帮助：

function [s, g, f] = trace_projection_evaluation(I, R, T, P)
% I: image to be evaluated
% R: reference image
% T: translation vector (x, y) for aligning I with R
% P: projection vector (theta) for aligning I with R
% s: similarity score
% g: gradient of similarity score
% f: transformed image

% convert I and R to double precision grayscale images
I = im2double(rgb2gray(I));
R = im2double(rgb2gray(R));

% rotate and translate I using P and T
Tform = affine2d([cosd(P) -sind(P) 0; sind(P) cosd(P) 0; T(1) T(2) 1]);
I = imwarp(I, Tform, 'OutputView', imref2d(size(R)));

% calculate similarity score s
s = sum(sum(I .* R)) / sqrt(sum(sum(I .^ 2)) * sum(sum(R .^ 2)));

% calculate gradient of similarity score g
g = zeros(2, 1);
for i = 1:2
    % calculate gradient of I in direction i
    if i == 1
        [dx, dy] = gradient(I);
    else
        [dy, dx] = gradient(I);
    end
    
    % rotate and translate gradient of I using P and T
    dx = imwarp(dx, Tform, 'OutputView', imref2d(size(R)));
    dy = imwarp(dy, Tform, 'OutputView', imref2d(size(R)));
    
    % calculate gradient of similarity score in direction i
    g(i) = 2 * sum(sum((dx .* R + I .* dy) .* R)) / sqrt(sum(sum(I .^ 2)) * sum(sum(R .^ 2)));    
end

% calculate transformed image f
f = imwarp(I, Tform, 'OutputView', imref2d(size(R)));
end

该代码实现了寻踪投影评价法的三个步骤：旋转和平移，计算相似度得分和梯度。输入参数包括待评估的图像 I、参考图像 R、平移向量 T 和旋转角度 P。输出结果包括相似度得分 s、相似度得分的梯度 g 和变换后的图像 f。

注意：该代码仅供参考，具体实现应根据具体需求进行调整。