A constrained formulation for compressive spectral image reconstruction using linear mixture models

Bacca, Jorge; Vargas, Hector; Argüello, Henry

doi:10.1109/camsap.2017.8313122

Cited by 6 publications

(2 citation statements)

References 22 publications

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“…where A is the composite sensing matrix that modules function is minimized [14,18]. The optimization problem is given Equation.28 as…”

Section: Measurement Hardware Strategymentioning

confidence: 99%

“…For instance, recent works have shown good results with as few as 20% of compressed measurements [9][10][11] which would reduce by 80% the acquisition time of traditional methods. The techniques of compressive sensing imaging (CSI) are able to reconstruct the image from an underdetermined system of linear equation that describes the measurement acquisition process [12,13], by choosing an appropriate representation basis where the image presents sparse behavior [14].…”

Section: Introductionmentioning

confidence: 99%

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Single Pixel Compressive Spectral Polarization Imaging using a Movable Micro-Polarizer Array

Bacca-Quintero

Vargas-García

Molina-Velasco

et al. 2018

Rev. Fac. Ing. Univ. Antioquia

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The acquisition of spectral polarization images is a method that obtains polarized, spectral and spatial information of a scene. Traditional acquisition methods use dynamic elements that capture all the information of a scene, by scanning the areas of interest, which result in large amounts of data proportional to the desired image resolution. Hence, in this work, the compression of spectral polarization images using a single pixel architecture, that uses a micro-polarizer array aligned with a binary coded aperture is proposed. The micro-polarizer is moved horizontally in each shot, so that diverse types of codifications from the scene are obtained. The proposed architecture allows several compressive 2D projections with spatial, spectral and polarization coding to be obtained. Stokes parameter images at several wavelengths are reconstructed. This architecture reduces the total number of measurements needed to obtain spectral polarization images compared to traditional acquisition methods. The experiments validate the quality of the architecture obtaining 43.19 dB, 37.49 dB and 30.41 dB of the peak signal-to-noise ratio for the first three Stokes parameters respectively. RESUMEN: La adquisición de imágenes espectro polarizadas es un método que obtiene información espacial, espectral y de polarización de una escena. Los métodos tradicionales de adquisición utilizan elementos dinámicos que capturan la totalidad de la información de la escena, escaneando las áreas de interés. Esto resulta en grandes cantidades de datos proporcionales a la resolución de imagen deseada. Por esta razón, en este trabajo se propone la compresión de imágenes espectro polarizadas usando una arquitectura óptica de único píxel, que usa un arreglo de micro-polarizadores alineados con una apertura codificada binaria. El arreglo de micro-polarizadores es movido horizontalmente en cada captura, permitiendo lograr diversos tipos de codificaciones de la escena. La arquitectura propuesta permite obtener varias proyecciones 2-D comprimidas con codificación espacial, espectral y de polarización, para luego reconstruir los Parámetros de Stokes a varias longitudes de onda. Esta arquitectura reduce el numero total de medidas necesarias para obtener la información espectral y de polarización de las imágenes comparadas con las arquitecturas tradicionales. Los experimentos validad la calidad de la arquitectura propuesta obteniendo 43.19 dB, 37.49 dB y 30.41 dB de la proporción máxima de señal a ruido para los tres primeros de Stokes respectivamente.

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“…where A is the composite sensing matrix that modules function is minimized [14,18]. The optimization problem is given Equation.28 as…”

Section: Measurement Hardware Strategymentioning

confidence: 99%