Color categories revealed by non-negative matrix factorization of Munsell color spectra

Color categories revealed by non-negative matrix factorization of Munsell color spectra

Non-negative matrix factorization (NMF, Nature 401 (1999) 788-791) is a method to derive non-negative basis functions for sets of data that are inherently non-negative, such as color spectra. We applied NMF to Munsell color spectra and investigated the color names associated with the non-negative basis functions. NMF yields basis functions compatible with established color naming categories.

Relating reflectance spectra space to Munsell color appearance space.

The goal is to construct a simple model relating the conceptually defined Munsell color space to a physical representation of the relationship among the reflectance spectra obtained from the color chips comprising the Munsell color atlas. In the model both the Munsell conceptual system and the transformed reflectance spectra are shown to be well represented in Euclidean space, and the two space...

Overlapping spectra resolution using non-negative matrix factorization.

Non-negative matrix factorization (NMF), with the constraints of non-negativity, has been recently proposed for multi-variate data analysis. Because it allows only additive, not subtractive, combinations of the original data, NMF is capable of producing region or parts-based representation of objects. It has been used for image analysis and text processing. Unlike PCA, the resolutions of NMF ar...

Non-negative matrix factorization

Color categories and color appearance.

We examined categorical effects in color appearance in two tasks, which in part differed in the extent to which color naming was explicitly required for the response. In one, we measured the effects of color differences on perceptual grouping for hues that spanned the blue-green boundary, to test whether chromatic differences across the boundary were perceptually exaggerated. This task did not ...