In a previous post, I described how I had created a Matlab program to analyze sets of reflectance spectra, generate basis functions, and then use those basis functions to produce metamer sets, all with an arbitrary fixed color. For review, here is the methodology I used: Using principal component analysis, find a set of basis… [Read More]

In preparation for some work that I’ll be doing about observer metameric errors in digital cameras, I’ve built a program that, given a target color and a set of sample reflectance spectra, will: Using principal component analysis, find a set of basis functions for the sample set Assuming the set is lit with a particular… [Read More]

A DPR PS&T member kindly supplied me with a collection of reflectance spectra about 220 natural objects. I added that set to my other patch sets, and performed a principal component analysis (PCA) on each set. One thing I did differently this time is I restricted the wavelengths under consideration to the set between 400… [Read More]

Using the natural reflectance spectra that a DPR PS&T member supplied me, and illuminating all the samples with D50 light, I looked at the errors with an optimized compromise matrix generated by training on the CC24, the CC SG, the CC Passport, and the natural spectra themselves. As expected, training on the natural spectra was… [Read More]

After constructing the software tools to get the results for  the last few posts, it occurred to me that I’d done most of the work to take a crack at something that had always interested me, but I’d never gotten around to researching: do camera color filter arrays (CFAs) that produce more accurate results when… [Read More]