RT Journal Article
T1 Parallel Implementation of the CCSDS 1.2.3 Standard for Hyperspectral Lossless Compression
A1 Bascones García, Daniel
A1 González Calvo, Carlos
A1 Mozos Muñoz, Daniel
AB Hyperspectral imaging is a technology which, by sensing hundreds of wavelengths per pixel, enables fine studies of the captured objects. This produces great amounts of data that require equally big storage, and compression with algorithms such as the Consultative Committee for Space Data Systems (CCSDS) 1.2.3 standard is a must. However, the speed of this lossless compression algorithm is not enough in some real-time scenarios if we use a single-core processor. This is where architectures such as Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs) can shine best. In this paper, we present both FPGA and OpenCL implementations of the CCSDS 1.2.3 algorithm. The proposed paralellization method has been implemented on the Virtex-7 XC7VX690T, Virtex-5 XQR5VFX130 and Virtex-4 XC2VFX60 FPGAs, and on the GT440 and GT610 GPUs, and tested using hyperspectral data from NASA’s Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS). Both approaches fulfill our real-time requirements. This paper attempts to shed some light on the comparison between both approaches, including other works from existing literature, explaining the trade-offs of each one.
PB MDPI
SN 2072-4292
YR 2017
FD 2017-09-21
LK https://hdl.handle.net/20.500.14352/19221
UL https://hdl.handle.net/20.500.14352/19221
LA eng
NO Ministerio de Ciencia e Innovación (MICINN)
DS Docta Complutense
RD 6 abr 2025