Repositorio
Institucional

Meza, Pablo

Ortiz, Ivan#Vera, Esteban#Martinez, Javier

Compressive hyperspectral imaging recovery by spatial-spectral non-local means regularization

OPTICAL SOC AMER

OPTICS EXPRESS

en

Hyperspectral imaging systems can benefit from compressed sensing to reduce data acquisition demands. We present a new reconstruction algorithm to recover the hyperspectral datacube from limited optically compressed measurements, exploiting the inherent spatial and spectral correlations through non-local means regularization. The reconstruction process is solved with the help of split Bregman optimization techniques, including penalty functions defined according to the spatial and spectral properties of the scene and noise sources. For validation purposes, we also implemented a compressive hyperspectral imaging system that relies on a digital micromirror device and a near-infrared spectrometer, where we obtained enhanced and promising reconstruction results when using our proposed technique in contrast with traditional compressive image reconstruction. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Artículo original

Fondo Nacional de Desarrollo Cientifico y Tecnologico (FONDECYT) (11140605, 11150476).

Fondo Nacional de Desarrollo Científico y Tecnológico (FONDECYT) (11140605, 11150476).

10.1364/OE.26.007043

pdf

http://dx.doi.org/10.1364/OE.26.007043

Optics

Óptica

Matemáticas Aplicadas

Ciencias de la Computación

version publicada

dorada

acceso abierto

acceso abierto

WOS:000427900400064

Compressive hyperspectral imaging recovery by spatial-spectral non-local means regularization

Artículo original

OPTICAL SOC AMER

OPTICS EXPRESS

Óptica

1094-4087

en

ANID FONDECYT 11140605#ANID FONDECYT 11150476

ANID FONDECYT 11140605

ANID FONDECYT 11150476

Fondo Nacional de Desarrollo Cientifico y Tecnologico (FONDECYT) (11140605, 11150476).

pdf

894

901