Longwave infrared (LWIR) coded aperture dispersive spectrometer

Fernández, C.; Guenther, B. D.; Gehm, Michael E.; Brady, David J.; Sullivan, M. E.

doi:10.1364/oe.15.005742

Cited by 21 publications

(8 citation statements)

References 9 publications

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“…The implementation of snapshot HTS could be turned into a multiplexing coding spectrometer ( Fig. 3), if the non-dispersive imaging path is not considered, described in [4,[16][17][18]. The measurement problem of dispersive imaging path in traditional HTS [4,[16][17][18] can be described as:…”

Section: Implementation Of Snapshot Multiplex Spectrometermentioning

confidence: 99%

“…Besides, it is the mostly used coding matrix in multiplexing, based on which a static, multimodal, multiplex spectrometer (MMS) is proposed [16]. In MMS, based on compressed sensing (CS), Nonnegative least-squares (NNLS) [16][17][18] method is employed to reconstruct the spectrum of the scene. It could realize a snapshot measurement keeping high-throughput advantage, and even estimate spectral images of target.…”

Section: Introductionmentioning

confidence: 99%

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High-SNR snapshot multiplex spectrometer with sub-Hadamard-S matrix coding

Zhao

Bai

Han

et al. 2019

Optics Communications

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We present a robust high signal-to-noise ratio (SNR) snapshot multiplex spectrometer with sub-Hadamard-S matrix coding. We demonstrated for the first time that the sub-Hadamard-S matrix coding could provide comparable SNR improvement with Hadamard-S matrix in Hadamard transform spectrometer (HTS). Normally, HTS should change the coding mask to obtain a reasonable spectrum result, causing unexpected time-consuming. An extra imaging path to collect the light intensity of the aperture is added in this paper. Both light intensity of the aperture and overlapped spectra are captured within one shot, turning Hadamard-S matrix coding into sub-Hadamard-S matrix coding. Simulations and experiments show that the proposed method could obtain comparable SNR improvement with the traditional HTS, maintaining snapshot.

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Section: Implementation Of Snapshot Multiplex Spectrometermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High-SNR snapshot multiplex spectrometer with sub-Hadamard-S matrix coding

Zhao

Bai

Han

et al. 2019

Optics Communications

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“…Efforts to apply CS in the LWIR spectral region include those by Fernandez et al [1] who explored the feasibility of a coded aperture LWIR HSI system. This approach employs an FPA to simultaneously capture spectral and spatial data in a single frame and boasts improved throughput relative to traditional grating based systems.…”

Section: Capability Overviewmentioning

confidence: 99%

Longwave infrared compressive hyperspectral imager

Dupuis

Kirby

Cosofret

2015

Next-Generation Spectroscopic Technologies VIII

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Physical Sciences Inc. (PSI) is developing a longwave infrared (LWIR) compressive sensing hyperspectral imager (CS HSI) based on a single pixel architecture for standoff vapor phase plume detection. The sensor employs novel use of a high throughput stationary interferometer and a digital micromirror device (DMD) converted for LWIR operation in place of the traditional cooled LWIR focal plane array. The CS HSI represents a substantial cost reduction over the state of the art in LWIR HSI instruments. Radiometric improvements for using the DMD in the LWIR spectral range have been identified and implemented. In addition, CS measurement and sparsity bases specifically tailored to the CS HSI instrument and chemical plume imaging have been developed and validated using LWIR hyperspectral image streams of chemical plumes. These bases enable comparable statistics to detection based on uncompressed data.In this paper, we present a system model predicting the overall performance of the CS HSI system. Results from a breadboard build and test validating the system model are reported. In addition, the measurement and sparsity basis work demonstrating the plume detection on compressed hyperspectral images is presented.Key Words: Compressive sensing, hyperspectral imager, sparsity basis, single pixel camera TECHNOLOGY OVERVIEW Capability OverviewStandoff chemical vapor detection in the longwave infrared (LWIR) spectral range is currently dominated by high-priced interferometric systems, including the single pixel Joint Services Lightweight Standoff Chemical Agent Detector (JSLSCAD) and the Bruker Rapid as well as the imaging Telops HyperCam and Adaptive Infrared Imaging Spectroradiometer (AIRIS). The JSLSCAD employs an FTIR modulator and scanning mirrors to obtain a spatially coarse data cube acquired over 360° in azimuth and -10 to +50° in elevation. AIRIS employs a tunable Fabry-Perot filter and a LWIR FPA to acquire the data cube. Similar technologies are present in the HyperCam. The fundamental limitation of these systems with regard to wider deployment is the multiple $100k price. Secondary limitations include large size, interferometric moving parts, slow acquisition speed, and large data bandwidth. All of these factors can be mitigated with a low-cost hyperspectral sensor based on compressive sensing (CS) in a single pixel architecture.Efforts to apply CS in the LWIR spectral region include those by Fernandez et al [1] who explored the feasibility of a coded aperture LWIR HSI system. This approach employs an FPA to simultaneously capture spectral and spatial data in a single frame and boasts improved throughput relative to traditional grating based systems. However, the use of a LWIR FPA will limit cost reduction of this particular solution. An attempt has been made to integrate a tunable (Fabry-Perot) filter with a CS solution in the LWIR [2] with limited success in terms of performance, primarily owing to diffraction by the digital micromirror device (DMD) employed as a spatial light modulator (SLM). PSI in cooperation ...

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“…Both imagers are completely static, single-shot designs, resulting in mechanically robust and inexpensive systems. In these respects the system architectures are a descendant of the coded-aperture spectroscopy architecture previously developed by several of the current authors [44][45][46][47][48]. In our first extension to spectral imaging [43], however, the implementation required a sequence of exposures in order to measure the contents of the spectral data cube.…”

Section: Compressive Spectral Imagingmentioning

confidence: 99%

Compressive Optical Imaging Systems - Theory, Devices and Implementation

Baraniuk¹,

Brady²,

Kelly³

et al. 2009

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Standard Form 298 Prescribed by ANSI-Std Z39-18 REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)Rice University 6100 Main St. MS 16 Houston TX 77005 PERFORMING ORGANIZATION REPORT NUMBER SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)Dennis Healy DARPA, Microsystems Technology Office 3701 N. Fairfax Dr. Arlington VA 22203-1714 SPONSOR/MONITOR'S ACRONYM(S)DARPA MTO/SPAWAR SPONSORING/MONITORING AGENCY REPORT NUMBER DISTRIBUTION AVAILABILITY STATEMENTApproved for public release; distribution is unlimited SUPPLEMENTARY NOTES ABSTRACTIn this project we expanded the theory of compressive sensing and explored the connection of CS to advanced optical imaging systems. In regard to theory we incorporated a Hidden Markov Tree signal model into existing CS theory and produced an algorithm for fast signal recover.We physically implemented CS on a single-pixel imaging testbed and analyzed its performance against existing multiplexing schemes. The insight of CS theory and experience in CS implementation culminated with the creation of our single-shot hyperspectral imager. SUBJECT TERMSanalog-to-information conversion, compressive sampling, sparsity, random filter, random sampling

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Longwave infrared (LWIR) coded aperture dispersive spectrometer

Cited by 21 publications

References 9 publications

High-SNR snapshot multiplex spectrometer with sub-Hadamard-S matrix coding

High-SNR snapshot multiplex spectrometer with sub-Hadamard-S matrix coding

Longwave infrared compressive hyperspectral imager

Compressive Optical Imaging Systems - Theory, Devices and Implementation

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