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fast and adaptive lossless on-board hyperspectral data compression system for space applicationsEfficient on-board lossless hyperspectral data compression reduces the data volume necessary to meet NASA and DoD limited downlink capabilities. The techniques also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware, which makes it practical for flight implementations of pushbroom instruments. A prototype of the compressor (and decompressor) of the algorithm is available in software, but this implementation may not meet speed and real-time requirements of some space applications. Hardware acceleration provides performance improvements of 10x-100x vs. the software implementation (about 1M samples/sec on a Pentium IV machine). This paper describes a hardware implementation of the JPL-developed 'Fast Lossless' compression algorithm on a Field Programmable Gate Array (FPGA). The FPGA implementation targets the current state of the art FPGAs (Xilinx Virtex IV and V families) and compresses one sample every clock cycle to provide a fast and practical real-time solution for Space applications.
Document ID
Document Type
Conference Paper
External Source(s)
Aranki, Nazeeh
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Bakhshi, Alireza
(B&A Engineering Systems, Inc. Costa Mesa, CA, United States)
Keymeulen, Didier
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Klimesh, Matthew
(Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
May 18, 2015
Publication Date
March 7, 2009
Subject Category
Computer Systems
Meeting Information
2009 IEEE Aerospace Conference(Big Sky, MT)
Distribution Limits
image compression
FPGA compressor