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