From Color Sensor Space to Feasible Reflectance Spectra

TLDR: This paper proposes a solution to correct the outcome of a generic recovery method, in order to take into account quality constrains, and assumes the smoothness of the solution of the recovery method is implicit from the adoption of linear models to represent reflectance functions.

Abstract: The interaction of light and object surfaces generates color signals in the visible band that are responsible for digital acquisition system outputs. Inverting this mapping from the sensor space back to the wavelength domain is of great interest for many applications. Since 1964, with the idea of Cohen to exploit the characteristic of smoothness of surface reflectance functions, a lot of work has been done in the analysis, synthesis and recovering of spectral information using linear models. The general use of such models is for the establishment of a one-to-one relationship between sensor's data and reflectance spectrum, with the requirement of ensuring the quality of the recovered spectrum in terms of physical feasibility and naturalness. In this paper, we propose a solution to correct the outcome of a generic recovery method, in order to take into account quality constrains. Our strategy assumes the smoothness of the solution of the recovery method, an assumption implicitly satisfied from the adoption of linear models to represent reflectance functions.