任務:
現在有兩來自於stereo-camera拍攝的兩幅圖像:
左圖, flowers-left.png 右圖,flowers-right.png:

現在在左圖中取一個大小爲100*100的patch.

在右圖的strip中尋找匹配的patch.

在此使用 ( sum of square differences )SSD算法進行匹配。也可以使用cross-correlation.
Matlab 程序代碼:
% Load images
left = imread('imgs/flowers-left.png');
right = imread('imgs/flowers-right.png');
figure, imshow(left);
figure, imshow(right);
% Convert to grayscale, double, [0, 1] range for easier computation
left_gray = double(rgb2gray(left)) / 255.0;
right_gray = double(rgb2gray(right)) / 255.0;
% Define image patch location (topleft [row col]) and size
patch_loc = [120 170];
patch_size = [100 100];
% Extract patch (from left image)
patch_left = left_gray(patch_loc(1):(patch_loc(1) + patch_size(1) - 1), patch_loc(2):(patch_loc(2) + patch_size(2) - 1));
figure, imshow(patch_left);
% Extract strip (from right image)
strip_right = right_gray(patch_loc(1):(patch_loc(1) + patch_size(1) - 1), :);
figure, imshow(strip_right);
% Now look for the patch in the strip and report the best position (column index of topleft corner)
best_x = find_best_match(patch_left, strip_right);
disp(best_x);
patch_right = right_gray(patch_loc(1):(patch_loc(1) + patch_size(1) - 1), best_x:(best_x + patch_size(2) - 1));
figure, imshow(patch_right);
% Find best match
% Use sum of square differences (SSD), you could also use cross-correlation
function best_x = find_best_match(patch, strip)
% TODO: Find patch in strip and return column index (x value) of topleft corner
best_x = 1; % placeholder
min_diff = Inf;
[row_strip, col_strip]=size(strip);
[row_patch, col_patch]=size(patch);
for x = 1:(col_strip - col_patch + 1 )
other_patch = strip(:, x:(x + col_patch -1 ));
diff = sum(sqrt((patch -other_patch).^2), 'all');
% diff = sumsq((patch - other_patch)(:)); %octave
if diff < min_diff
min_diff = diff;
best_x = x;
end
end
end
結果:
右圖爲在右圖中匹配等到的結果。

来源:https://www.cnblogs.com/yubao/p/12427349.html