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Title: A novel highly parallel algorithm for the detection and tracking of chemical gas plumes using hyperspectral video sequences
Authors: Díaz Martín, María 
Chanussot, Jocelyn
Guerra, Raul 
Lopez, Sebastian 
Sarmiento, Roberto 
Bertozzi, Andrea L.
UNESCO Clasification: 3307 Tecnología electrónica
3325 Tecnología de las telecomunicaciones
Keywords: Change Detection
Gas Plume
Hyperspectral Imaging
Real-Time Applications
Tracking, et al
Issue Date: 2018
Conference: 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2018 
Abstract: Multitemporal hyperspectral images provide detailed spectral information that makes them particularly suitable for the detection and tracking of chemical gas plumes. However, due to the high dimensionality of the data to process, classical video processing techniques do not ensure a real-time performance, which makes imperative the development of new advanced and computationally efficient algorithms. In this paper, we propose a novel method for the detection and tracking of chemical gas plumes, recorded in hyperspectral video sequences, which has been specially designed for being easily parallelizable in hardware devices for applications under realtime constraints. The identification of the gas plume presence has been tackled as a spectral change detection problem using the temporal redundancy of two consecutive frames. To maximize spectral differences, the first derivative of each frame pixel is computed and compared with its homologous pixel in the next frame measuring the spectral angle between them. We have applied the proposed methodology to two real video sequences. The results obtained support the benefits of our proposal.
ISBN: 9781728115818
ISSN: 2158-6276
DOI: 10.1109/WHISPERS.2018.8747197
Source: Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing [ISSN 2158-6276], v. 2018-September
Appears in Collections:Actas de congresos
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