Selection of filters for multispectral acquisition using the filter vectors analysis method

One of the most important components in a multispectral acquisition system is the set of optical filters that allow acquisition in different bands of the visible light spectrum. Typically, either a rather large set of traditional optical filters or a tunable filter capable of many different configurations are employed. In both cases, minimising the actual number of filters used while keeping the error sufficiently low is important to reduce operational costs, acquisition time, and data storage space. In this paper, we introduce the Filter Vectors Analysis Method for choosing an optimal subset of filters / filter configurations among those available for a specific multispectral acquisition system. This method is based on a statistical analysis of the data resulting from an acquisition of a representive target, and tries to identify those filters that yield the most information in the given environmental conditions. We have compared our method with a simple method (ESF, for 'evenly spaced filters') that chooses filters so that their transmittance peak wavelengths are as evenly spaced as possible within the considered spectrum. The results of our experiments suggest that the Filter Vectors Analysis Method method can not bring substantial improvements over the ESF method, but also indicate that the ideas behind our method deserve further investigation