In a previous work [Appl. Opt.44, 5688 (2005)] we found the optimum sensors for a planned multispectral system for measuring skylight in the presence of noise by adapting a linear spectral recovery algorithm proposed by Maloney and Wandell [J. Opt. Soc. Am. A3, 29 (1986)]. Here we continue along these lines by simulating the responses of three to five Gaussian sensors and recovering spectral information from noise-affected sensor data by trying out four different estimation algorithms, three different sizes for the training set of spectra, and various linear bases. We attempt to find the optimum combination of sensors, recovery method, linear basis, and matrix size to recover the best skylight spectral power distributions from colorimetric and spectral (in the visible range) points of view. We show how all these parameters play an important role in the practical design of a real multispectral system and how to obtain several relevant conclusions from simulating the behavior of sensors in the presence of noise.

Many spectral-recovery methods using RGB digital cameras assume the underlying smoothness of illuminant and reflectance spectra, and apply low-dimensional linear models. The aim of the present work was to test whether a direct-mapping method could be used instead of a linear-models approach to recover spectral radiances and reflectances from natural scenes with an RGB digital camera and colored filters. In computer simulations, a conventional RGB digital camera with up to three colored filters was used to image scenes drawn from a hyperspectral image database. Three measures were used to evaluate recovery with the direct-mapping method: goodness-of-fit, root-mean-square error, and a color-difference metric. It was found that with two and three filters both spectral radiances and reflectances could be recovered sufficiently accurately for many practical applications. With little increase in computational complexity, an RGB camera and a few colored filters can provide significantly better recovery of natural scenes than an RGB camera alone.

The commercialization of EnChroma glasses has generated great expectations for people to be able to see new colors or even correct color vision deficiency (CVD). We evaluate the effectiveness of these glasses using two complementary strategies for the first time. The first consists of using the three classical types of tests-recognition, arrangement and discrimination-with and without glasses, with a high number of individuals. In the second, we use the spectral transmittance of the glasses to simulate the appearance of stimuli in a set of scenes for normal observers and observers with CVD. The results show that the glasses introduce a variation of the perceived color, but neither improve results in the diagnosis tests nor allow the observers with CVD to have a more normal color vision.

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Performance of multispectral devices in recovering spectral data has been intensively investigated in some applications, as in spectral characterization of art paintings, but has received little attention in the context of spectral characterization of natural illumination. This study investigated the quality of the spectral estimation of daylight-type illuminants using a commercial digital CCD camera and a set of broadband colored filters. Several recovery algorithms that did not need information about spectral sensitivities of the camera sensors nor eigenvectors to describe the spectra were tested. Tests were carried out both with virtual data, using simulated camera responses, and real data obtained from real measurements. It was found that it is possible to recover daylight spectra with high spectral and colorimetric accuracy with a reduced number of three to nine spectral bands.

In our ongoing research on the effectiveness of different passive tools for aiding Color Vision Deficiency (CVD) subjects, we have analyzed the VINO 02 Amp Oxy-Iso glasses using two strategies: 1) 52 observers were studied using four color tests (recognition, arrangement, discrimination, and color-naming); 2) the spectral transmittance of the lenses were used to model the color appearance of natural scenes for different simulated CVD subjects. We have also compared VINO and EnChroma glasses. The spectral transmission of the VINO glasses significantly changed color appearance. This change would allow some CVD subjects, above all the deutan ones, to be able to pass recognition tests but not the arrangement tests. To sum up, our results support the hypothesis that glasses with filters are unable to effectively resolve the problems related to color vision deficiency.

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The acquisition of spectral reflectance factor image data in an outdoor environment is a challenging task, mostly due to nonstatic scene content and illumination. In this work, we propose a work-flow for this task using a commercial Bragg-grating-based hyperspectral imager that can capture the visible and near-infrared part of the light spectrum. To our knowledge, we are the first who use this technology for outdoor spectral reflectance factor imaging. The work-flow involves focus position and exposure time estimation, illumination scaling, and image registration, among other procedures. Most of them generally apply to hyperspectral imaging, while some are specific to a Bragg-grating-based hyperspectral imaging device when dealing with specific challenges in outdoor environments. We have conducted some experiments to evaluate the quality of the acquired image data and discussed some limitations of the technology for spectral imaging of outdoor scenes. Fourteen urban scene spectral images acquired using the proposed approach are already publicly available to the scientific community under a Creative Commons license.