Comments on: Four Color Images

By: Jake

Jake — Sun, 05 Apr 2009 22:53:29 +0000

I really like the VIVID colormap, especially for contour type plots.
http://www.mathworks.com/matlabcentral/fileexchange/20848

By: Bob

Bob — Thu, 02 Apr 2009 18:06:47 +0000

FYI, an implementation of some Light-Bartlein colormaps is available on the File Exchange.
http://www.mathworks.com/matlabcentral/fileexchange/17555

By: Rob Henson

Rob Henson — Thu, 26 Mar 2009 16:11:17 +0000

KMEANS clustering is a nice way to pick the colours.

[c,ctrs] = kmeans(double(Ic(:)),4,’Distance’,’sqeuc’);
imshow(reshape(c,size(Ic)),cm);

By: Jody Klymak

Jody Klymak — Thu, 26 Mar 2009 15:56:10 +0000

I updated my page so it is not such a mess.

I don’t think there is anything inherently wrong with jet. However, I would love to see some of the other Light and Bartlein colormaps made part of matlab, and included in the tutorials. IBM seems to have stalled out on some of this research, but there is enough of it in the public domain that the Mathworks could make some progress.

By: Loren

Loren — Thu, 26 Mar 2009 14:04:47 +0000

Thanks Jonas and Jeff for some more great article links. It’s really worthwhile to take a look at them.

–Loren

By: Jeff Mather

Jeff Mather — Thu, 26 Mar 2009 13:33:23 +0000

I’m glad to see people talking about making colormaps that faithfully represent the data. It’s a big pet peeve of mine to see bad colormaps. (I know this has little to do with the Shep Fairey part of your post. . . .)

After creating the colors for your colormap, you may want to run some MATLAB code to preview how it will look for the 5% of the population that has some form of color confusion: Color Universal Design and a MATLAB-based Simulator.

By: Jonas

Jonas — Thu, 26 Mar 2009 12:18:26 +0000

I have been using either grayscale or “perceptual colormaps” as discussed in http://www.research.ibm.com/people/l/lloydt/color/color.HTM ever since I read that article.
It is amazing how much difference a colormap makes in interpreting data. Check for example peaks (or abs(peaks)) with jet vs grayscale and notice how you are being influenced by the colors.

By: Loren

Loren — Thu, 26 Mar 2009 11:32:00 +0000

Thanks for all the comments! Yes, there are lots of ways to divide the data into bins and Cris shows one that makes the bins approximately equal. I think some will find Jody’s colormap illustration useful too.

There are no plans to change jet. If you know of particular research or a particular colormap, feel free to point us to it.

–Loren

By: Cris Luengo

Cris Luengo — Thu, 26 Mar 2009 08:29:33 +0000

Hi Loren,

Instead of manually finding the 3 thresholds you use to divide up the gray-values, you could do something like this. It will find values such that each color gets the same number of pixels:

h=hist(double(Ic(:)),0:255);
ch=cumsum(h);
levels(2)=find(ch<(ch(end)*1/4),1,’last’)-1;
levels(3)=find(ch<(ch(end)*2/4),1,’last’)-1;
levels(4)=find(ch<(ch(end)*3/4),1,’last’)-1;

Talking about color maps, is there any interest at The MathWorks to change the colormap generated by `jet`? It has some very strong bands at yellow and cyan, the blue section is way longer than the red one, and there hardly is any green (which is the color we’re best at distinguishing different shades of). Not that I know how to do it better, but I’m sure there has been quite a bit of research on this over the years.

Cheers,
Cris.

By: Jody Klymak

Jody Klymak — Thu, 26 Mar 2009 00:42:26 +0000

Inspired by Light and Bartlein I made a mess of colormaps. The write up is partly a mess, and the code worse, but I’ll post it here for others to play with.

http://web.uvic.ca/~jklymak/perceptcmap/TestColor.html

perceptcmap.tgz

I basically use colCog.m whenever I have data that goes from negative to positive, and I want zero to be washed out. Does much better than jet or a jet-derivative that replaces green w/ white at the middle. A number of colleagues use bright red to bright blue as well (Ts3Shears.jpg) but that always seems to draw my eye to the red more than the blue.