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This code snippet converts a 2D matrix to a 3D matrix where the values in the 3rd dimension correspond to pixel intensity in the red, green, and blue domains. This is the format used by many functions in the Image Processing Toolbox (which is not required for this function to run).The code works by mapping the values of matrix "mat" onto the rows of colormap "cmap" using a fast vectorised operation. function im=mat2im(mat,cmap,maxVal) PURPOSE Uses vectorized code to convert matrix "mat" to an m-by-n-by-3 image matrix which can be handled by the Mathworks image-processing functions. The the image is created using a specified color-map and, optionally, a specified maximum value. Note that it discards negative values! INPUTS mat - an m-by-n matrix cmap - an m-by-3 color-map matrix. e.g. hot(100). If the colormap has few rows (e.g. less than 20 or so) then the image will appear contour-like. limits - by default the image is normalised to it's max and min values so as to use the full dynamic range of the colormap. Alternatively, it may be normalised to between limits(1) and limits(2). Nan values in limits are ignored. So to clip the max alone you would do, for example, [nan, 2] OUTPUTS im - an m-by-n-by-3 image matrix Example 1 - combine multiple color maps on one figure clf, colormap jet, r=rand(40); subplot(1,3,1),imagesc(r), axis equal off , title('jet') subplot(1,3,2),imshow(mat2im(r,hot(100))) , title('hot') subplot(1,3,3),imshow(mat2im(r,summer(100))), title('summer') colormap winter %changes colormap in only the first panel Example 2 - clipping p=peaks(128); J=jet(100); subplot(2,2,1), imshow(mat2im(p,J)); title('Unclipped') subplot(2,2,2), imshow(mat2im(p,J,[0,nan])); title('Remove pixels 0') subplot(2,2,4), imshow(mat2im(p,J,[-1,3])); title('Plot narrow pixel range') Rob Campbell - April 2009 See Also: ind2rgb
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Windows Software
Albina Merfyn - I find this to be really easy to use. I can...
