Computational Spectral Imaging With Diffractive Lenses And Spectral Filter Arrays

Abstract

Computational spectral imaging aims to reconstruct the entire 3D spectral cube from a few compressive measurements. Recently different spectral imaging modalities have been developed by exploiting the wavelength-dependent behavior of diffractive lenses. Another line of development in this area is provided by spectral filter arrays which has enabled multispectral sensors. In this work, we develop a new compressive spectral imaging modality by exploiting a diffractive lens with a multi-spectral sensor. To reconstruct the spectral cube from these compressive measurements, a model-based fast sparse recovery algorithm is also developed. The performance of the proposed technique is illustrated for the visible range using different spectral filter array configurations and number of measurements. The results demonstrate that significant performance improvement can be achieved over a recent imaging technique with diffractive lenses, while also enabling snapshot imaging with simpler and more compact designs.

Experimental Analysis of Tunable Optical Spectral Imaging System Using a Grating in the Pupil Function

“…Herein, we present an HSI system with the capability of acquiring the spectral images of an object over the desired spectral band by finely tuning the wavelength of acquisition. The proposed optical system offers the versatility to obtain spectral and hyperspectral imaging at a low cost compared to acousto-optic systems [44][45], where equipment like monochromators, wavelength filters, liquid crystal technology [46][47] and acousto-optic filters or modulators are used [48]. Our system avoids the use of these costly instruments.…”