Plot of mean square error [EDIT]

If this be the formula for MSE for RGB images A,B of same size 256*200, then how to obtain a line plot for every pixel with x axis representing pixels and y axis representing the MSE values

MSE = reshape(mean(mean((double(A) - double(B)).^2,2),1),[1,3])

There are only t开发者_Python百科wo images A ,B. The plot should illustrate change between each pixel of A and B which is meant by MSE.

If you want to display the changes "between each pixel" then what you're showing is not mean squared errors any more -- there's no averaging going on. (Unless you intend to average across the three colour planes, but I don't recommend that: changes in R,G,B are not equally salient to the human visual system. If you really must do this, you might want to weight them, say, 2:4:1 for something a bit more representative, but this is still ad hoc and not likely to give a very accurate idea of what differences will look biggest.)

Of course it's perfectly reasonable to want to see the per-pixel errors, but I wouldn't recommend using a line plot to display them; it's likely to be confusing rather than informative. Rather, display them as an image:

errs = (double(A)-double(B)).^2;
image(errs / max(errs(:)));
axis image;

which you can then compare by eye with A and B to see what image regions/features/... correspond to worse errors. The brightness and colour of each pixel indicate the amount of error and how it's distributed across the R, G, and B planes.

On the other hand, perhaps what you actually need is mean squared error over individual rows, or columns, of the image. In that case, after creating errs as above, use mean to compute the row or column means; that will give you a 256-by-1-by-3 image or a 1-by-200-by-3 image; now I would suggest plotting R,G,B curves separately unless you (probably foolishly in my opinion, as mentioned above) insist on averaging the planes.

row_errs = mean(errs,2); % this is now of size [n,1,3]

now row_errs(:,:,1) is a vector of MS-across-rows red errors, row_errs(:,:,2) is a vector of MS-across-rows green errors, etc. You can feed these to plot.