Spatially heterodyned snapshot imaging spectrometer.

Snapshot hyperspectral imaging Fourier transform (SHIFT) spectrometers are a promising technology in optical detection and target identification. For any imaging spectrometer, spatial, spectral, and temporal resolution, along with form factor, power consumption, and computational complexity are often the design considerations for a desired application. Motivated by the need for high spectral resolution systems, capable of real-time implementation, we demonstrate improvements to the spectral resolution and computation trade-space. In this paper, we discuss the implementation of spatial heterodyning, using polarization gratings, to improve the spectral resolution trade space of a SHIFT spectrometer. Additionally, we employ neural networks to reduce the computational complexity required for data reduction, as appropriate for real-time imaging applications. Ultimately, with this method we demonstrate an 87% decrease in processing steps when compared to Fourier techniques. Additionally, we show an 80% reduction in spectral reconstruction error and a 30% increase in spatial fidelity when compared to linear operator techniques.

[1]  Martin Fodslette Møller,et al.  A scaled conjugate gradient algorithm for fast supervised learning , 1993, Neural Networks.

[2]  D. M. Titterington,et al.  Neural Networks: A Review from a Statistical Perspective , 1994 .

[3]  Andrew Harvey,et al.  Birefringent Fourier-transform imaging spectrometer. , 2004, Optics express.

[4]  M. Descour,et al.  Large-image-format computed tomography imaging spectrometer for fluorescence microscopy. , 2001, Optics express.

[5]  M. Kudenov,et al.  Fabrication of ideal geometric-phase holograms with arbitrary wavefronts , 2015 .

[6]  George A. Vanasse,et al.  Correction of Asymmetric Interferograms Obtained in Fourier Spectroscopy , 1966 .

[7]  E. Dereniak,et al.  Compact real-time birefringent imaging spectrometer. , 2012, Optics express.

[8]  Fred L. Roesler,et al.  Spatial heterodyne spectroscopy for the exploration of diffuse interstellar emission lines at far-ultraviolet wavelengths , 1992 .

[9]  Jiangtao Xi,et al.  Neural network digital fringe calibration technique for structured light profilometers. , 2007, Applied optics.

[10]  Ashwin A. Wagadarikar,et al.  Single disperser design for coded aperture snapshot spectral imaging. , 2008, Applied optics.

[11]  Kunihiko Fukushima,et al.  A neural network for visual pattern recognition , 1988, Computer.

[12]  Michael W Kudenov,et al.  Spatial heterodyne interferometry with polarization gratings. , 2012, Optics letters.

[13]  Siegfried Janz,et al.  Optical fiber interferometer array for scanless Fourier-transform spectroscopy. , 2013, Optics letters.

[14]  Colm P. O'Donnell,et al.  Hyperspectral imaging – an emerging process analytical tool for food quality and safety control , 2007 .

[15]  Michael W. Kudenov,et al.  Compact snapshot real-time imaging spectrometer , 2011, Security + Defence.

[16]  Liang Gao,et al.  Snapshot hyperspectral retinal camera with the Image Mapping Spectrometer (IMS) , 2011, Biomedical optics express.

[17]  Jean-Claude Diels,et al.  Concerning the Spatial Heterodyne Spectrometer. , 2016, Optics express.

[18]  Heterodyne Fourier Transform Spectroscopy using Moving Diffraction Grating , 2001 .

[19]  Kazuhiko Oka,et al.  White-light channeled imaging polarimeter using broadband polarization gratings. , 2011, Applied optics.

[20]  B.M. Wilamowski,et al.  Neural network architectures and learning algorithms , 2009, IEEE Industrial Electronics Magazine.

[21]  Michael Egmont-Petersen,et al.  Image processing with neural networks - a review , 2002, Pattern Recognit..

[22]  M. Descour,et al.  Computed-tomography imaging spectrometer: experimental calibration and reconstruction results. , 1995, Applied optics.

[23]  Yang Yintang,et al.  Improved neural network based scene-adaptive nonuniformity correction method for infrared focal plane arrays. , 2008 .

[24]  N. Borrelli,et al.  Imaging and radiometric properties of microlens arrays. , 1991, Applied optics.

[25]  Donald D Duncan,et al.  Measurement of oxygen saturation in the retina with a spectroscopic sensitive multi aperture camera. , 2008, Optics express.

[26]  L. Mertz,et al.  Auxiliary computation for Fourier spectrometry , 1967 .

[27]  Bruce M. Swinyard,et al.  Herschel SPIRE fourier transform spectrometer: calibration of its bright-source mode , 2014, 1401.2045.

[28]  David A. Luo,et al.  Neural network calibration of a snapshot birefringent Fourier transform spectrometer with periodic phase errors. , 2016, Optics express.

[29]  M. Dewhirst,et al.  Hyperspectral imaging of hemoglobin saturation in tumor microvasculature and tumor hypoxia development. , 2005, Journal of biomedical optics.

[30]  Kazuyoshi Itoh,et al.  Application of Measurement multiple-image fourier of fast phenomena transform spectral imaging to measurement of fast phenomena , 1994 .

[31]  Michael W. Kudenov,et al.  Review of snapshot spectral imaging technologies , 2013, Optics and Precision Engineering.

[32]  Ning Wang,et al.  Detecting chilling injury in Red Delicious apple using hyperspectral imaging and neural networks , 2009 .

[33]  Robert Sundberg,et al.  Development of a hyperspectral scene generator , 2003, SPIE Optics + Photonics.

[34]  Gonzalo R. Arce,et al.  Compressive Hyperspectral Imaging via Approximate Message Passing , 2015, IEEE Journal of Selected Topics in Signal Processing.

[35]  Quan Min Zhu,et al.  A Correlation-Test-Based Validation Procedure for Identified Neural Networks , 2009, IEEE Transactions on Neural Networks.

[36]  Michael W. Kudenov,et al.  Phase correction algorithms for a snapshot hyperspectral imaging system , 2015, SPIE Optical Engineering + Applications.

[37]  Michael J. Escuti,et al.  Polarization spatial heterodyne interferometer: model and calibration , 2014 .

[38]  Yifan Zhang,et al.  A Bayesian Restoration Approach for Hyperspectral Images , 2012, IEEE Transactions on Geoscience and Remote Sensing.