I don't quite understand what you want, you have a 3D matrix which is 412x314x200 and you want to get a 1x200 vector where each element i is the mean of a page in the original matrix? like this:
vector(i) = mean(matrix(:,:,i))
For that you can use mean like this:
vector = mean(mean(matrix,1),2)
Or maybe you want to get one 412x314 image which is the mean along the third dimension of the matrix, like this:
new_image = mean(matrix,3)
Or maybe you want to take each page of the 3D matrix and smooth it, then return it to the matrix and/or calculate some value from it?
If this is what you want to do though I suggest you look at imfilter or filter2, because movmean only works for vectors. You could use something like this to average filter each page of your 412x314x200 matrix:
input_matrix = rand(412,314,200);
average_window = 10;
average_filter = fspecial('average',[average_window average_window]);
B = imfilter(input_matrix,average_filter);
figure
subplot(1,2,1)
imagesc(input_matrix(:,:,1))
title('original (:,:,1)')
subplot(1,2,2)
imagesc(B(:,:,1))
title('average smoothed (:,:,1)')
Then you will have to decide what you want to do with that.
Like movmean and other smoothing functions imfilter needs to know the 'filter size', this is the size of the window over which it should work. For instance if the filter size is 11 then every pixel in the smoothed image is the average of the 11x11 square of pixels surrounding it in the original.
Hope this helps,
M.
