How to calculate the mean value of the 3rd dimension of YUV so as to filter the differences between consecutive frames ?

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awa 2016-7-6

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评论： Image Analyst 2016-7-7

I was trying to resolve the issue of non-consecutive frames which extracted from a video. I want to go through each pixel and each frame.

Currently I have converted the RGB images to YUV and extracted each component. I want to calculate the mean value of the 3rd dimension of YUV so as to filter the difference between consecutive frames. . What should I do next ?

Thank you.

Below are the code that I have done so far: =================================================

caffe.reset_all();
caffe.set_mode_gpu();
caffe.set_device(0);
clear; close all;
close all;
clear;
%%Display RGB
Dir = 'C:\Users\Image\'; 
im_list = dir(fullfile(Dir, '*.bmp'));
% loop for all test images
for i = 1:length(im_list)
im_path = [Dir im_list(1).name];
x  = imread(im_path);
R=x(:,:,1); 
G=x(:,:,2); 
B=x(:,:,3); 
RGB = cat(3,R,G,B);
YUV = rgb2ycbcr(RGB);
%%Display each component
compY = YUV(:,:,1);   %%extract Y component
compU = YUV(:,:,2);   %%extract U component
compV = YUV(:,:,3);    %%extract V component

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Joss Knight 2016-7-6

编辑：Joss Knight 2016-7-6

I don't understand the question. The channels are the third dimension, so the mean in the third dimension is the mean of all channels (which you get from rgb2gray), not just the Y channel.

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Answer 1

Thorsten 2016-7-6

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编辑：Thorsten 2016-7-6

在 MATLAB Online 中打开

meanY = mean(compV(:));

or if you have the Image Processing Toolbox:

meanY = mean2(YUV(:,:,3));

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awa 2016-7-7

Thanks for your kind help.

I have modified my questions. Could you please help to take a look at again ?

Thank you.

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Answer 2

Image Analyst 2016-7-7

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在 MATLAB Online 中打开

It's still ambiguous what you mean by "third dimension". Thorsten gave you one way. The third channel/slice/plane of your 3D color space image is compV, and mean2() will take the mean of that color channel (the value channel).

meanV = mean2(compV); % A single scalar value.

Whereas

meanImage = mean(YUV, 2); % A 2-D image.

will give you an image where each pixel is the mean along the third dimension. So, the result is an image that is (compY+compU+compV)/3.

Which concept is what you're thinking of?

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awa 2016-7-7

在 MATLAB Online 中打开

Hi ImageAnalyst,

I added below code to my previous code above. Could you please help to check whether I can do like this ?

[a,b,c] = size(x);  %%a by b by c arrays
meanFrame = zeros(size(x));
sumFrame = 0;
% 
 for i = 1:a  %for each pixel
    for j = 1:b
        for k =1:c  %%for each frame
           sumFrame = sumFrame+k;
        end 
      meanFrame = sumFrame/k;
    end
 end
imshow(meanFrame);