LCR-spectrometer-Scientific-Reports.pdf (original) (raw)

Compressive Sensing Hyperspectral Imaging by Spectral Multiplexing with Liquid Crystal

Journal of Imaging, 2019

Hyperspectral (HS) imaging involves the sensing of a scene’s spectral properties, which are often redundant in nature. The redundancy of the information motivates our quest to implement Compressive Sensing (CS) theory for HS imaging. This article provides a review of the Compressive Sensing Miniature Ultra-Spectral Imaging (CS-MUSI) camera, its evolution, and its different applications. The CS-MUSI camera was designed within the CS framework and uses a liquid crystal (LC) phase retarder in order to modulate the spectral domain. The outstanding advantage of the CS-MUSI camera is that the entire HS image is captured from an order of magnitude fewer measurements of the sensor array, compared to conventional HS imaging methods.

Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder

Scientific Reports, 2016

Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

Compressed Sensing for Multidimensional Spectroscopy Experiments

The Journal of Physical Chemistry Letters, 2012

Compressed sensing is a processing method that significantly reduces the number of measurements needed to accurately resolve signals in many fields of science and engineering. We develop a two-dimensional variant of compressed sensing for multidimensional spectroscopy and apply it to experimental data. For the model system of atomic rubidium vapor, we find that compressed sensing provides an order-ofmagnitude (about 10-fold) improvement in spectral resolution along each dimension, as compared to a conventional discrete Fourier transform, using the same data set. More attractive is that compressed sensing allows for random undersampling of the experimental data, down to less than 5% of the experimental data set, with essentially no loss in spectral resolution. We believe that by combining powerful resolution with ease of use, compressed sensing can be a powerful tool for the analysis and interpretation of ultrafast spectroscopy data.

Single-pixel spectroscopy via compressive sampling

Classical Optics 2014, 2014

Recently we presented a method for compressive spectrometry based on a liquid crystal cell. Here we describe the spectrum reconstruction dependence on the type of sparsifier used in the reconstruction process.

Applications of integrated sensing and processing in spectroscopic imaging and sensing

Journal of Chemometrics, 2005

Integrated sensing and processing (ISP) encompasses the use of optical computing and adapted excitation signals to physically implement chemometric calculations in spectroscopic sensors for imaging. As data sets become larger and more complex with each emerging generation of hyperspectral imagers, the 'pixel-to-pupil' ratio increases at a rate faster than computing power can accommodate. In response to the need for faster and more efficient methods of processing, many analog solutions to the problem of high data dimensionality have emerged. The successful development of ISP has strong implications for military imaging, biosensing, spectroscopic imaging, and pharmaceutical process analytical technology (PAT). ISP developments in spectroscopy and PAT have emerged as alternatives to conventional Fourier transform infrared (FT-IR), near-infrared (NIR), IR, UV-visible, fluorescence, Raman, and acoustic-resonance spectrometry (ARS). Flourishing applications of ISP have demonstrated predictive ability equivalent to conventional approaches for sample differentiation and analyte quantification, in only a fraction of the time required for traditional spectrometric measurements.

Single disperser design for compressive, single-snapshot spectral imaging

Recent theoretical work in "compressed sensing" can be exploited to guide the design of accurate, single-snapshot, static, high-throughput spectral imaging systems. A spectral imager provides a three-dimensional data cube in which the spatial information of the image is complemented by spectral information about each spatial location. In this paper, compressive, single-snapshot spectral imaging is accomplished via a novel static design consisting of a coded input aperture, a single dispersive element and a detector. The proposed "single disperser" design described here mixes spatial and spectral information on the detector by measuring coded projections of the spectral datacube that are induced by the coded input aperture. The single disperser uses fewer optical elements and requires simpler optical alignment than our dual disperser design. We discuss the prototype instrument, the reconstruction algorithm used to generate accurate estimates of the spectral datacubes, and associated experimental results.

Multichannel Spectral Imaging System for Measurements with the Highest Signal-to-Noise Ratio

Optical Review, 1997

A multichannel spectral imaging system consisting of dichroic mirrors is proposed. The system is expected to have the highest signal-to-noise ratio (SNR) because of the largest optical throughput realized by the multichannel configurations for both imaging and spectrometry. A multichannel spectral imaging system with eight spectral bands was designed by the evolutionary algorithms and then fabricated. The SNR is studied and compared experimentally with those of other fast spectral imaging techniques. A time-sequence of spectral images of a super-continuum light beam is measured using the present system. The number of spectral channels of the system is limited chiefly by the difflculty in designing the arrangement of dichroic mirrors and the optical performance of those mirrors. These limitations restrict the number of spectral channels to approximately 16 at present.

Compressed sensing for multidimensional electronic spectroscopy experiments

2012

Compressed sensing is a processing method that significantly reduces the number of measurements needed to accurately resolve signals in many fields of science and engineering. We develop a two-dimensional (2D) variant of compressed sensing for multidimensional electronic spectroscopy and apply it to experimental data. For the model system of atomic rubidium vapor, we find that compressed sensing provides significantly better resolution of 2D spectra than a conventional discrete Fourier transform from the same experimental data. We believe that by combining powerful resolution with ease of use, compressed sensing can be a powerful tool for the analysis and interpretation of ultrafast spectroscopy data.

Improvement of spectral resolution by spectroscopic imaging

Applied Magnetic Resonance, 2004

We propose to use three-dimensional spectroscopic imaging (SI) to increase the spectral resolution for biological samples for which strong susceptibility effects (or poor magnetic homogeneity) cause significant line broadening. Due to susceptibility effects (or poor field homogeneity) the SI voxel spectra even from a uniform sample are shifted with respect to each other and much less broadened than the total sample spectrum. Realignment of the spectra from individual voxels prior to their coaddition produces a total-volume spectrum with significantly narrower lines.