Abstract

Computational hyperspectral cameras with broadband encoded filter arrays enable high precision spectrum reconstruction with only a few filters. However, these types of hyperspectral cameras have limited application, because it is difficult for conventional encoded filter arrays to balance among the spectrum regulation capacity, angle insensitivity, and processibility. This Letter presents a new, to the best of our knowledge, encoded filter composed of superposition Fabry–Perot resonance cavity (SFP) that can simultaneously take all three aspects into consideration. By learning the parameters of an SFP encoder and a neural network decoder in an end-to-end manner, a computational hyperspectral camera based on an SFP filter array presents up to 2.24 times higher spectral reconstruction accuracy, 10 times wider working angle, and can be produced with a low-cost manufacturing process.

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