Spectrum reconstruction for filter-array spectrum sensor from sparse template selection

In recent years, miniature spectrometers have been found to be useful in many applications to resolve spectrum signatures of materials. In this paper, algorithms are proposed to realize a miniature spectrometer using a low-cost filter-array spectrum sensor. Conventionally, the filter-array spectrum sensor can be modeled as an overdetermined problem, and the spectrum can be reconstructed by solving a set of linear equations. In this paper, we instead model the spectrum reconstruction process as an underdetermined problem, and bring up the concept of template-selection by sparse representation. l1 − norm minimization is introduced to achieve a high reconstruction resolution. Both simulation and experimental results show that a superior quality of spectrum reconstruction can be made possible from the presented underdetermined approach.