Spectrum reconstruction for filter-array spectrum sensor using sparse representation

摘要

In recent years, miniature spectrometers have been found useful in many applications to resolve spectrum signature of objects or materials. In this paper, algorithms for filter-array spectrum sensor to realize miniature spectrometers are investigated. Conventionally, the filter-array spectrum sensor can be modeled as an over-determined problem, and the spectrum can be reconstructed by solving a set of linear equations. On the contrary, we model the spectrum reconstruction process as an under-determined problem, and bring up the concept of template-selection by sparse representation. L1-minimization algorithm is tested to achieve a high reconstruction resolution. Simulation results show superior quality of spectrum reconstruction can be made possible from this under-determined approach