Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/57516
Title: Real-Time Hyperspectral Image Compression onto Embedded GPUS
Authors: Díaz Martín, María 
Guerra Hernández, Raúl Celestino 
Horstrand, Pablo
Martel Jordán, Ernestina Ángeles 
López Suárez, Sebastián 
López Feliciano, José Francisco 
Sarmiento Rodríguez, Roberto 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: CUDA
Embedded systems
Hyperspectral compression
Lossy compression
Low-power graphical processing units (LPGPUs), et al
Issue Date: 2019
Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 
Abstract: Real-time hyperspectral imaging on-board compression represents a critical processing step in many remote sensing applications where the acquired hyperspectral data need to be efficiently stored and/or transferred. However, the complexity of the compression algorithms as well as the volume of data to be compressed and the limited computational resources of the hardware devices available on-board turn the real-time compression into a very challenging task. This paper presents a low-power-consumption solution for real-time lossy compression of hyperspectral images. The lossy compression algorithm for hyperspectral image system (HyperLCA) compressor has been implemented onto two NVIDIA Jetson developer kits. These NVIDIA boards include low-power embedded graphic processing units, which allow parallel programing for speeding up the compression process at a reasonable low power consumption. The experiments carried out in this paper are oriented to the necessities imposed by a specific smart farming application although all drawn conclusions are extrapolable to other fields in which remotely sensed hyperspectral images are to be compressed in real time. The obtained results verify both the good performance of the HyperLCA compressor for the targeted application and the achievement of a real-time performance by using the developed implementations. Additionally, several comparisons and conclusions have been drawn from the experiments in relation to the different strategies employed for accelerating the compression process.
URI: http://hdl.handle.net/10553/57516
ISSN: 1939-1404
DOI: 10.1109/JSTARS.2019.2917088
Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing [ISSN 1939-1404], v. 12 (8), p. 2792-2809
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