How to create a disparity map?

Question

Okay so I have implemented a stereo correspondence algorithm which takes a stereo image pair, matches a point on the left image with a point on the right image, and finds the disparity between the points. I need to write this to a disparity map.

The disparity maps I have found are grayscale images, with lighter grays meaning less depth and darker grays meaning more depth. How do I translate my set of disparities into a grayscale image like this? My disparities are very small, ie only a distance of two between pixels, how does this translate into a grayscale pixel value?

There must be a standard way of compiling disparity maps but all my searching has yielded nothing thus far.

Answer 1

A simple solution when creating a disparity map the largest distance becomes black ie rgb(0,0,0) and the smallest distance - which is 0 - becomes white ie rgb(255,255,255). If you divide 255 by the largest distance then you find the increment value. Finally just go through all the disparities and set each rgb value to 255 minus the disparity times the increment value. Viola, you have your disparity map.

So in your example it sounds like your largest distance is only 2 pixals (which unfortunately means your map isn't going to have a lot of detail). Anyways 255 / 2 = 127.5. This means that 127.5 is the increment value. So everywhere that the disparity is 0, the rgb value is 255 - (0 * 127.5) or rgb(255,255,255), anywhere the disparity is 1 the rgb value is 255 - (1 * 127.5), we'll round to 128 so rgb(128,128,128) and anywhere the disparity is 2 the rgb value is 255 - (2 * 127.5) or rgb(0,0,0).

Here are some more resources:
How MathWorks does it
Jay Rambhia has a good blog explaining how to program one
Hope that helps!