Compressive Sensing Hyperspectral Imaging by Spectral Multiplexing with Liquid Crystal (original) (raw)
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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.
Along-track scanning using a liquid crystal compressive hyperspectral imager
Optics express, 2016
In various applications, such as remote sensing and quality inspection, hyperspectral (HS) imaging is performed by spatially scanning an object. In this work, we present a new compressive hyperspectral imaging method that performs along-track scanning. The method relies on the compressive sensing miniature ultra-spectral imaging (CS-MUSI) system, which uses a single liquid crystal (LC) cell for spectral encoding and provides a more efficient way of HS data acquisition, compared to classical spatial scanning based systems. The experimental results show that a compression ratio of about 1:10 can be reached. Owing to the inherent compression, the captured data is preprepared for efficient storage and transmission.
Single-pixel optical sensing architecture for compressive hyperspectral imaging
Compressive hyperspectral imaging systems (CSI) capture the threedimensional (3D) information of a scene by measuring two-dimensional (2D) coded projections in a Focal Plane Array (FPA). These projections are then exploited by means of an optimization algorithm to obtain an estimation of the underlying 3D information. The quality of the reconstructions is highly dependent on the resolution of the FPA detector, which cost grows exponentially with the resolution. High-resolution low-cost reconstructions are thus desirable. This paper proposes a Single Pixel Compressive Hyperspectral Imaging Sensor (SPHIS) to capture and reconstruct hyperspectral images. This optical architecture relies on the use of multiple snapshots of two timevarying coded apertures and a dispersive element. Several simulations with two different databases show promising results as the reliable reconstruction of a hyperspectral image can be achieved by using as few as just the 30% of its voxels.
Single Aperture Spectral+ToF Compressive Camera: Towards Hyperspectral+Depth Imagery
IEEE Journal of Selected Topics in Signal Processing, 2017
Spectral imaging involves the sensing of a large amount of spatial information across a multitude of wavelengths. Conventional approaches rely on scanning techniques to construct a spectral data cube. Recently, compressive spectral imaging (CSI) has allowed to estimate spectral images with as few as a single coded snapshot. On a different front, 3D ranging imaging often involves scanning along one of the spatial dimensions to estimate the depth of an scene using structured light, or the use of two cameras as required by stereo-imaging techniques. Recently, Time-of-Flight (ToF) snapshot imaging has gained considerable attention, due to its accuracy and speed. To date, however, these imaging modalities (CSI and ToF) have been realized and implemented by separate independent imaging sensors. This paper presents the development of a single aperture compressive spectral + depth imaging camera that employs a commodity 3D range ToF sensor as the sensing device of a coded-aperture-based compressive spectral imager. The proposed system uses a single aperture/single sensor, thus representing a significant improvement over existing RGB+D cameras that integrate two separate image sensors, one for RGB and another for depth. In addition, the observable wavelength range of the CSI device is expanded from the visible to the near-infrared, resolving up to as many as 16 independent channels. The proposed system allows the addition of side-information by placing a grayscale or RGB camera in the same path of the single-aperture system, such that the quality of the spectral estimation is improved, while maintaining high-frame rates. We demonstrate the proposed ideas through real experimentation conducted on an assembled CSI+ToF testbed camera system.
Compressive sensing and hyperspectral imaging
Compressive sensing (sampling) is a novel technology and science domain that exploits the option to sample radiometric and spectroscopic signals at a lower sampling rate than the one dictated by the traditional theory of ideal sampling. The possibility of undersampling a signal without losing significant information is founded on the signal characteristic of admitting a sparse mathematical representation, which can be made accessible to an instrument throughout a specific integral transformation to be performed with a dedicated optical subsystem. This technology belongs to the general field of signal compression, and its main feature is connected with the circumstance that compression takes place before signal registration, during the sampling phase. Due to this characteristic, compressive sensing promises exceptional savings for sensor design and realization in terms of the required memory for temporary data storage, bandwidth necessary for data transmission, electrical power consu...
Spatial versus spectral compression ratio in compressive sensing of hyperspectral imaging
Compressive Sensing II, 2013
Compressive hyperspectral imaging is based on the fact that hyperspectral data is highly redundant. However, there is no symmetry between the compressibility of the spatial and spectral domains, and that should be taken into account for optimal compressive hyperspectral imaging system design. Here we present a study of the influence of the ratio between the compression in the spatial and spectral domains on the performance of a 3D separable compressive hyperspectral imaging method we recently developed. Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/01/2013 Terms of Use: http://spiedl.org/terms Proc. of SPIE Vol. 8717 87170G-2 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/01/2013 Terms of Use: http://spiedl.org/terms Proc. of SPIE Vol. 8717 87170G-9 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/01/2013 Terms of Use: http://spiedl.org/terms
Scientific Reports
In this paper, we present a new hyperspectral compact camera which is designed to have high spatial and spectral resolutions, to be vibrations tolerant, and to achieve state-of-the-art high optical throughput values compared to existing nanosatellite hyperspectral imaging payloads with space heritage. These properties make it perfect for airborne and spaceborne remote sensing tasks. The camera has both hyperspectral and panchromatic imaging capabilities, achieved by employing a wedge-shaped liquid crystal cell together with computational image processing. The hyperspectral images are acquired through passive along-track spatial scanning when no voltage is applied to the cell, and the panchromatic images are quickly acquired in a single snapshot at a high signal-to-noise ratio when the cell is voltage driven.
Engineering Proceedings
This paper describes the activities related to a feasibility study for an Earth observation optical payload, operating in the medium infrared, based on super-resolution and compressive sensing techniques. The presented activities are running in the framework of the ASI project SISSI, aiming to improve ground spatial resolution and mitigate saturation/blooming effects. The core of the payload is a spatial light modulator (SLM): a bidimensional array of micromirrors electronically actuated. Thanks to compressive sensing approach, the proposed payload eliminates the compression board, saving mass, memory and energy consumption.
Applied optics, 2018
A hyperspectral imaging system based on compressed sensing has been developed to image in the 0.9-2.5 μm shortwave infrared wavelengths. With a programmable digital micromirror device utilized as spatial light modulator, we have successfully performed spectrally resolved image reconstruction with a 256-element InGaAs linear array detector without traditional raster scanning or a push-broom mechanism by a compressed sensing (CS) single-pixel camera approach. The chemical sensitivity of the imaging sensor to near-infrared (NIR) overtone signatures of hydrocarbons was demonstrated using hydrocarbon and ink patterns on glass, showing spectral selectivity for the chemical components. Compared to point-by-point raster scanning, we show that the CS scheme can effectively accelerate image acquisition with lower but reasonable quality.