Optimal sensitivity design of multispectral camera via broadband absorption filters based on compressed sensing

Abstract

Spectrum acquisition of imaging scenes with super spectral resolution can be realized by multichannel spectral camera with broadband absorption filters under the condition that the multichannel spectral camera sensitivity is optimized. Algorithms to broadband absorption filters selection to optimize the camera sensitivity proposed in the past have no strict theoretical guarantees on reconstruction accuracy. Consequently, the insight had not been uncovered until the Compressive Sensing (CS) theory has ripped in the last recent years. Combined the proofed datasets of published literature and sensing matrix design theory of CS algorithm to optimal the sensitivity of multispectral camera by filter selection is proposed and verified. The more variation of filter vectors can be selected, the more accuracy of the spectral reconstruction results can be acquired with super resolution.