Video rate spectral imaging using a coded aperture snapshot spectral imager

Wagadarikar, Ashwin A.; Pitsianis, Nikos P.; Sun, Xiaobai; Brady, David J.

doi:10.1364/oe.17.006368

Cited by 295 publications

(165 citation statements)

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“…A spatial section of N × N pixels with N = 128, L = 8 spectral bands and D = 8 frames was used for simulations. Specifically, the L selected wavelengths were 0 = 400, 1 = 440, 2 = 480, 3 = 520, 4 = 560, 5 = 600, 6 = 640 and 7 = 680 nm. For the numerical simulation of the video C-CASSI system illustrated in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Further, the C-CASSI extended to video (video C-CASSI) is a spectral multiplexing sensor that allows capturing spectral dynamic scenes, or spectral video, by projecting each spectral frame onto a bidimensional detector [4,5,6]. A spectral video is considered as a four-dimensional signal ( , , , ), where , denote the spatial pixels, represents the spectral dimension and denotes the temporal component.…”

Section: Introductionmentioning

confidence: 99%

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Multiresolution-based reconstruction for compressive spectral video sensing using a spectral multiplexing sensor

León-López¹,

Galvis-Carreño²,

Arguello-Fuentes³

2018

revuin

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Este artículo puede compartirse bajo la licencia CC BY-ND 4.0 y se referencia usando el siguiente formato: K. León, L. Galvis, H. Arguello, "Multiresolution-based reconstruction for compressive spectral video sensing using a spectral multiplexing sensor," Rev. UIS Ing., vol. 17, no. 1, pp. 209-216, 2018. Doi: https://doi.org/10.18273/revuin.v17n1-2018020 Vol. 17, no. 1, pp. 209-216, enero-junio 2018 Revista UIS Ingenierías ABSTRACTSpectral multiplexing sensors based on compressive sensing attempt to break the Nyquist barrier to acquire high spectral resolution scenes. Particularly, the colored coded aperture-based compressive spectral imager extended to video, or video C-CASSI, is a spectral multiplexing sensor that allows capturing spectral dynamic scenes by projecting each spectral frame onto a bidimensional detector using a 3D coded aperture. Afterwards, the compressed signal reconstruction is performed iteratively by finding a sparse solution to an undetermined linear system of equations. Even though the acquired signal can be recovered from much fewer observations by an ℓ 2 − ℓ 1 -norm recovery algorithm than using conventional sensors, the reconstruction exhibits diverse challenges originated by the temporal variable or motion. The motion during the reconstruction produces artifacts that damages the entire data. In this work, a multiresolution-based reconstruction method for compressive spectral video sensing is proposed. In this way, it obtains the temporal information from the measurements at a low computational cost. Thereby, the optimization problem to recover the signal is extended by adding temporal information in order to correct the errors originated by the scene motion. Computational experiments performed over four different spectral videos show an improvement up to 4dB in terms of peak-signal to noise ratio (PSNR) in the reconstruction quality using the multiresolution approach applied to the spectral video reconstruction with respect to the traditional inverse problem. KEYWORDS:Multiresolution reconstruction; compressive spectral video; optimization. RESUMENLos sensores de multiplexación espectral basados en muestreo compresivo intentan romper la barrera de Nyquist para adquirir escenas de alta resolución espectral. Particularmente, el sistema de imágenes espectrales de única captura basado en aperturas codificadas de color extendido a vídeo, o video -CCASSI, es un sensor de multiplexación espectral que permite la adquisición de imágenes espectrales dinámicas proyectando cada fotograma espectral sobre un detector bidimensional usando un apertura de codificación 3D. Posteriormente, la reconstrucción de la señal 210 K. León, L. Galvis, H. Arguello comprimida se realiza iterativamente encontrando una solución escasa a un sistema lineal de ecuaciones indeterminado. Si bien la señal adquirida puede ser recuperada desde un algoritmo basado en la norma l_2 − l_1, con muchas menos observaciones en comparación a los sistemas convencionales, dicha reconstrucción presenta diversos desafíos originados p...

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiresolution-based reconstruction for compressive spectral video sensing using a spectral multiplexing sensor

León-López¹,

Galvis-Carreño²,

Arguello-Fuentes³

2018

revuin

View full text Add to dashboard Cite

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“…Snapshot cameras as the coded aperture snapshot spectral imager (CASSI) [3], its threedimensional version named colored coded aperture snapshot spectral imager (C-CASSI) [4], [5], the prism-mask video imaging spectrometry (PMVIS) [6], the snapshot colored compressive spectral imager (SCCSI) [7], and the single pixel camera spectrometry (SPCS) [8] are examples of CSI systems. There are other snapshot systems designed to capture spectral video, or spectral dynamic scenes, in a compressive format such as the single dispersive CASSI extended to video (video-CASSI) [9], the hybrid spectral video imaging system (HVIS) [10] and the high-speed hyperspectral (HSHS) [11] video acquisition. Furthermore, snapshot spectral systems such as C-CASSI, using random-colored coded apertures, have been extended to capture spectral images at video rates [12].…”

Section: Introductionmentioning

confidence: 99%

Spatio-spectro-temporal coded aperture design for multiresolution compressive spectral video sensing

Lopez

Galvis

Fuentes

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-Colored coded apertures (CCA) have been introduced in compressive spectral imaging (CSI) systems entailing richer coding strategies. CCA incorporate a wavelengthdependent coding procedure, which not only achieves spatial but also spectral coding in a single step. Even though the use of the CCA offers significant advantages and could also be applied to compressive spectral video sensing, this later application still exhibits diverse challenges originated by the temporal variable. The scene motion during the acquisition yields to motion artifacts such that these artifacts get aliased during the video reconstruction, damaging the entire data. As a result, multiresolution approaches have been proposed in order to alleviate the aliasing and enhance the video reconstruction. In this paper, it is proposed an algorithm to generate temporal colored coded aperture patterns that allow to sense the spatial, spectral and temporal information in an uniform way such that each spectral frame is spatially sensed at least once. In addition, it is proposed a multiresolution approach in the spectral multiplexing system allowing to extract optical flow estimates to address a higher quality reconstruction. Simulation results show an improvement up to 6 dB in terms of peak-signal to noise ratio (PSNR) in the reconstruction quality with the multiresolution approach using the designed patterns with respect to traditional random structures.

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“…The data cube is formed when computer algorithms invert this data [16,17] . Image-plane spatio-spectral coding is required to recover the image [18] . Inversion is often accompanied by noise amplification, a drawback of this type of system.…”

Section: Introductionmentioning

confidence: 99%

Novel, Noninvasive Multispectral Snapshot Imaging System to Measure and Map the Distribution of Human Retinal Vessel and Tissue Hemoglobin Oxygen Saturation

Firn

Khoobehi

2015

International Journal of Ophthalmic Research

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capillary mimicking a vessel. The quantitative calculations from the healthy subject, as well as the qualitative oxygen saturation maps, show oxygen saturation levels consistent with those in the literature. CONCLUSION: This system is clinically valuable for diagnosing and monitoring diseases affecting ocular oxygen saturation, such as glaucoma, diabetic retinopathy, age-related macular degeneration, and others. Our reliable method is capable of documenting tissue oxygenation throughout disease progression. © 2015 ACT. All rights reserved. INTRODUCTIONPathologic conditions in the retina and optic nerve head (ONH) can cause vision loss and blindness. Both structures have a high demand for oxygen, and loss of the normal oxygen supply through vascular insufficiency is believed to play an important role in diseases affecting the retina and ONH. Hypoxia of the retina and ONH is believed to be a factor in the development of ocular vascular disorders, such as diabetic retinopathy (DR), arteriovenous occlusion, and glaucoma. The ability to obtain relative measurements of oxygen saturation in the human ocular fundus could aid in the diagnosis and monitoring of these and other disorders. For example, measurement of changes in retinal and ONH oxygen saturation under controlled conditions could establish relationships among oxygen consumption, ABSTRACT AIM: To design and implement a snapshot imaging system capable of mapping oxygen saturation of retinal vessels and tissue clinically for the first time. MATERIALS AND METHODS: Our image-splitting design is attached to the imaging portions of a fundus camera. A relay subsystem and reimaging system convert reflected white light from the eye into seven monochromatic images simultaneously. Our algorithm uses intensity information at each of these discrete wavelengths to approximate the area between the oxy-and deoxyhemoglobin spectral curves, which has been shown to be proportional to oxygen saturation. We used MATLAB to convert this information into colorcoded oxygen saturation maps of the optic nerve head. We validated our system by using it on a model eye with a capillary of known blood oxygen saturation, then used it In vivo to obtain quantitative values of human oxygen saturation for veins and tissue. RESULTS: By collecting seven images simultaneously with one snapshot, our system is the first to document and reproducibly map oxygen saturation of the retinal vessels and tissue. Oxygen saturation values are color-coded, with oxygen-rich arteries in red, oxygen-poor veins in blue, and intermediate tissue yellow-green. Our system's calculations agree with co-oximeter readings of blood in a model eye

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Video rate spectral imaging using a coded aperture snapshot spectral imager

Cited by 295 publications

References 10 publications

Multiresolution-based reconstruction for compressive spectral video sensing using a spectral multiplexing sensor

Multiresolution-based reconstruction for compressive spectral video sensing using a spectral multiplexing sensor

Spatio-spectro-temporal coded aperture design for multiresolution compressive spectral video sensing

Novel, Noninvasive Multispectral Snapshot Imaging System to Measure and Map the Distribution of Human Retinal Vessel and Tissue Hemoglobin Oxygen Saturation

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