Ms. Laura V. Galvis Carreño Profile

Laura V. Galvis Carreño

at Univ of Delaware

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Proceedings Article | 20 February 2017 Paper

Side information in coded aperture compressive spectral imaging

Laura Galvis, Henry Arguello, Daniel Lau, Gonzalo Arce

Proceedings Volume 10117, 101170H (2017) https://doi.org/10.1117/12.2252167

KEYWORDS: Coded apertures, RGB color model, Imaging systems, Digital micromirror devices, Compressed sensing, Image compression, 3D image processing, Sensors, Reconstruction algorithms, Spatial light modulators

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Coded aperture compressive spectral imagers sense a three-dimensional cube by using two-dimensional projections of the coded and spectrally dispersed source. These imagers systems often rely on FPA detectors, SLMs, micromirror devices (DMDs), and dispersive elements. The use of the DMDs to implement the coded apertures facilitates the capture of multiple projections, each admitting a different coded aperture pattern. The DMD allows not only to collect the sufficient number of measurements for spectrally rich scenes or very detailed spatial scenes but to design the spatial structure of the coded apertures to maximize the information content on the compressive measurements. Although sparsity is the only signal characteristic usually assumed for reconstruction in compressing sensing, other forms of prior information such as side information have been included as a way to improve the quality of the reconstructions. This paper presents the coded aperture design in a compressive spectral imager with side information in the form of RGB images of the scene. The use of RGB images as side information of the compressive sensing architecture has two main advantages: the RGB is not only used to improve the reconstruction quality but to optimally design the coded apertures for the sensing process. The coded aperture design is based on the RGB scene and thus the coded aperture structure exploits key features such as scene edges. Real reconstructions of noisy compressed measurements demonstrate the benefit of the designed coded apertures in addition to the improvement in the reconstruction quality obtained by the use of side information.

Proceedings Article | 10 May 2016 Paper

Spectral dynamic scenes reconstruction based in compressive sensing using optical color filters

Kareth León, Laura Galvis, Henry Arguello

Proceedings Volume 9860, 98600D (2016) https://doi.org/10.1117/12.2224330

KEYWORDS: Coded apertures, Compressed sensing, Video, Video compression, Modulation, Staring arrays, Sensors, Video surveillance, RGB color model, Electroluminescent displays

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Spectral-temporal compressive imaging is a technique that allows to sense spatio-spectro-temporal information, known as spectral video from a single low-framerate monochrome measurement. Several optical architectures have been recently developed to capture the spectral features of a dynamic scene or spectral video based on the compressive sensing framework. These spectral-temporal compressive architectures are principally composed by four elements: a main lens, a coded aperture, a dispersive element and an FPA detector. Traditionally, these acquisition systems use block-unblock coded apertures that either block the light rays in the optical path or allow them to pass through. However, the modulation produced by the block-unblock coded apertures is wavelength independent, thus ignoring the highly correlated structure of the spectral information in a dynamic scene. In this work, the block-unblock coded apertures are replaced by colored coded apertures, whose pixels represent a set of specific optical filters such as low, high or band pass filters that modulate particular wavelengths of the scene. An analysis of the variations in the colored coded aperture pattern that allows to obtain improvements in PSNR compared with the block-unblock coded apertures is presented. Simulation results show an improvement up to 2 dB in the reconstruction quality with respect to the block-unblock coded apertures.

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