如何在 Matlab 中找到并突出显示图像中最亮的区域？

Question

亲爱的，

我想请求您的支持。我的目标是找到 RGB 图像中最亮的区域并在不使用其他工具的情况下突出显示它。请参阅下面的示例。

rgbImage = imread( 'Zoom1_WhiteImage.png' );
imshow(rgbImage);

[rows, columns, numberOfColorChannels] = size(rgbImage)

[x, y] = meshgrid(1:columns, 1:rows);
% Extract the individual red, green, and blue color channels.
% Need to cast to double or else x and y will be clipped to 255 when we concatenate them.
if numberOfColorChannels == 1
    % Leave as gray scale.
    % Get array listing [r, g, b, x, y].  Using (:) will turn all the 2-D arrays into column vectors.
    output = [rgbImage(:), x(:), y(:)];
else
    redChannel = double(rgbImage(:, :, 1));
    greenChannel = double(rgbImage(:, :, 2));
    blueChannel = double(rgbImage(:, :, 3));
    % Get array listing [r, g, b, x, y].  Using (:) will turn all the 2-D arrays into column vectors.
    output = [redChannel(:), greenChannel(:), blueChannel(:), x(:), y(:)];
end

[rows, columns] = find(rgbImage == 155);
imshow(rgbImage);
hold on

不幸的是，我正在为如何继续绘制应该覆盖灰色图像的点而苦苦挣扎。

请您帮我完成代码好吗？

Answer 1

我建议您阅读 MATLAB 中的逻辑索引 - 这是一个非常强大的概念，它允许您通过展平数组来跳过您尝试做的大部分事情，并使用 @ 创建单独的索引数组987654322@。例如，Here is an article 解决了底部向下的逻辑索引。

我已修改并添加到您的代码中，以便它使用逻辑索引来完成这项工作。我在 R2019b 中对此进行了测试。

rgbImage = imread( 'Zoom1_WhiteImage.png' );
imshow(rgbImage);

[rows, columns, numberOfColorChannels] = size(rgbImage)

% This is unnecessary - the 'find' command will generate the indices 
%   without you preparing a matrix of them:
% [x, y] = meshgrid(1:columns, 1:rows);   

if numberOfColorChannels == 1
    % No need to flatten the image, or combine it with indices:
    %output = [rgbImage(:), x(:), y(:)];

    brightness = rgbImage;  % For a 1 channel image, brightness is the same as the original pixel value.

else
%     redChannel = double(rgbImage(:, :, 1));
%     greenChannel = double(rgbImage(:, :, 2));
%     blueChannel = double(rgbImage(:, :, 3));
    % Get array listing [r, g, b, x, y].  Using (:) will turn all the 2-D arrays into column vectors.
%     output = [redChannel(:), greenChannel(:), blueChannel(:), x(:), y(:)];

    % For an RGB image, the brightness can be estimated in various ways, here's one standard formula: 
    brightness = (0.2126*rgbImage(:, :, 1) + 0.7152*rgbImage(:, :, 2) + 0.0722*rgbImage(:, :, 3));
end

% Establish a brightness threshold - pixels brighter than this value will
% be highlighted
threshold = 215;

% Create a zero-filled mask of equal size to the image to hold the
% information of which pixels met the brightness criterion:
mask = zeros(rows, columns, 'logical');

% Assign "1" to any mask pixels whose corresponding image pixel met the
% brightness criterion:
mask(brightness > threshold) = 1;

figure;
% Overlay and display mask. imoverlay was introduced in R2017, but the 
% syntax has changed a bit, so check the version you're using. You can also
% use imfuse, or imshowpair, or make your own image blending algorithm, 
% depending on how you want it to look.
imshow(imoverlay(rgbImage, mask, 'red'));
hold on