I've been exploring the use of an open-source image processing program developed by the National Institutes of Health (NIH) called ImageJ, and a related plug-in called DStretch. While RTI is very effective for examining texture, ImageJ and DStretch provide tools for analyzing color information, in addition to other capabilities, which can complement the use of RTI. (Image J and DStretch are Java-based programs, and you should check that you have installed the latest Java security update.) Both programs can be found easily by a simple search, or you can use the following links:
DStretch is short for "decorrelation stretch," an image enhancement technique originally developed at JPL for remote sensing applications. It has been successfully applied at rock art sites for identifying pictographs, where the composition consists primarily of pigments, as distinct from petroglyphs, which are defined by texture (apologies to archeologists for my loose definitions). An advantage of these tools over a proprietary program such as Photoshop is that they allow users to modify color-spaces in very specific, controlled ways, using defined algorithms. The Dstretch algorithm allows one to "reset" the image back to its original color values, so you can "undo" the effects of any filter you apply using the software. A more detailed explanation of the algorithms in DStretch is provided here:
The approach I'm using to integrate DStretch into RTI workflows is to process the RTIs first (creating a .ptm or .rti file), then use the RTIViewer to relight the image and apply PTM/RTI algorithms to bring out textural details. When I'm happy with the RTI image, I save a snapshot from the viewer. The snapshot can then be opened in ImageJ, and the DStretch algorithms can be applied to enhance color features. A limitation of this approach is that it's generally best to leave the colors unchanged when saving the image in the RTI Viewer. This can be done either by using the "default" setting or, if using Diffuse Gain or Specular Enhancement, by setting the "gain" or "Kd" controls at the positions that leave the most color in the image. This constrains the application of algorithmic enhancements in the RTIViewer somewhat, but it allows both textural and color features to be rendered in ways that are complementary.
Another approach, which might be preferable from a scientific perspective, is to process the images for color and texture using ImageJ/DStretch and RTI separately, and compare or combine the images using fade features available in other software. Keeping a log of how the images are processed would be very important, in any case. (Thanks to CHI Forums member Dr. George Bevan for pointing me to ImageJ and to Dr. Jon Harman for the DStretch plug-in.)