Abstract
The miniaturization of spectrometer can broaden the application area of spectrometry, which has huge academic and industrial value. Among various miniaturization approaches, filter-based miniaturization is a promising implementation by utilizing broadband filters with distinct transmission functions. Mathematically, filter-based spectral reconstruction can be modeled as solving a system of linear equations. In this paper, we propose an algorithm of spectral reconstruction based on sparse optimization and dictionary learning. To verify the feasibility of the reconstruction algorithm, we design and implement a simple prototype of a filter-based miniature spectrometer. The experimental results demonstrate that sparse optimization is well applicable to spectral reconstruction whether the spectra are directly sparse or not. As for the non-directly sparse spectra, their sparsity can be enhanced by dictionary learning. In conclusion, the proposed approach has a bright application prospect in fabricating a practical miniature spectrometer.
Highlights
Spectral analysis is an elementary and indispensable approach to the qualitative and quantitative analysis of chemical materials
We propose an algorithm of spectral reconstruction based on sparse optimization and dictionary learning
The main experimental instruments used in this work include a charge-coupled device (CCD) camera, a scientific grade spectrometer (PG2000 pro, Ideaoptics, Shanghai, China), an ultraviolet spectrophotometer (UV-2450, SHIMADZU, Kyoto, Japan), a halogen light source (HL-2000, Ocean Optics, Largo, FL, USA) and a light-emitting diode (LED) lamp
Summary
Spectral analysis is an elementary and indispensable approach to the qualitative and quantitative analysis of chemical materials. Photo crystal [5], linear variable optical filter [6], disordered photonic chip [7], dispersive hole array [8,9], micro interferometer array [10], liquid crystal phase retarder [11], multimode fiber [12,13], silicon multimode waveguide [14], broadband filter array [15,16,17,18,19,20] and so on are developed as the dispersive elements Among these various miniaturization technologies, the filter-based approach shows great potential in reducing the size as well as the cost of a spectrometer, which can enhance the portability and broaden the application area of spectrometry [15,16,17,18,19,20]
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