Recovering color from black and white photographs

This paper presents a mathematical framework for recovering color information from multiple photographic sources. Such sources could include either black and white negatives or photographic plates. This paper's main technical contribution is the use of Bayesian analysis to calculate the most likely color at any sample point, along with an expected error value. We explore the limits of our approach using hyperspectral datasets, and show that in some cases, it may be possible to recover the bulk of the color information in an image from as few as two black and white sources.