image - Matlab - 使用四个像素的平均值缩小图像

Question

我刚刚开始学习图像处理和 Matlab，我正在尝试使用平均 4 个像素缩小图像。这意味着对于每 4 个原始像素，我计算平均值并产生 1 个输出像素。到目前为止我有以下代码:

img = imread('bird.jpg');
row_size = size(img, 1);
col_size = size(img, 2);
res = zeros(floor(row_size/2), floor(col_size/2));
figure, imshow(img);
for i = 1:2:row_size
    for j = 1:2:col_size
        num = mean([img(i, j), img(i, j+1), img(i+1, j), img(i+1, j+1)]);
        res(round(i/2), round(j/2)) = num;
    end
end
figure, imshow(uint8(res));

此代码设法缩小图像，但将其转换为灰度。我知道我可能必须计算输出像素的 RGB 分量的平均值，但我不知道如何访问它们、计算平均值并将它们插入到结果矩阵中。

Answer 1

在 Matlab 中，RGB 图像被视为 3D 数组。您可以通过以下方式检查:

depth_size = size(img, 3)

depth_size =

     3

正如您所做的那样，循环解决方案在Sardar_Usama's answer中进行了解释。 。但是，在 Matlab 中，建议您在想要提高速度时避免循环。

这是一种矢量化解决方案，可将 RGB 图像缩小 n 倍:

img = imread('bird.jpg');
n = 2; % n can only be integer
[row_size, col_size] = size(img(:, :, 1));

% getting rid of extra rows and columns that won't be counted in averaging:
I = img(1:n*floor(row_size / n), 1:n*floor(col_size / n), :);
[r, ~] = size(I(:, :, 1));

% separating and re-ordering the three colors of image in a way ...
% that averaging could be done with a single 'mean' command:
R = reshape(permute(reshape(I(:, :, 1), r, n, []), [2, 1, 3]), n*n, [], 1);
G = reshape(permute(reshape(I(:, :, 2), r, n, []), [2, 1, 3]), n*n, [], 1);
B = reshape(permute(reshape(I(:, :, 3), r, n, []), [2, 1, 3]), n*n, [], 1);

% averaging and reshaping the colors back to the image form:
R_avg = reshape(mean(R), r / n, []);
G_avg = reshape(mean(G), r / n, []);
B_avg = reshape(mean(B), r / n, []);

% concatenating the three colors together:
scaled_img = cat(3, R_avg, G_avg, B_avg); 

% casting the result to the class of original image
scaled_img = cast(scaled_img, 'like', img); 

基准测试:

如果您想知道为什么矢量化解决方案更受欢迎，请看一下使用这两种方法处理 RGB 768 x 1024 图像需要多长时间:

------------------- With vectorized solution:
Elapsed time is 0.024690 seconds.

------------------- With nested loop solution:
Elapsed time is 6.127933 seconds.

因此，两种解决方案之间的速度差异超过 2 个数量级。