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High Compression of Infrared (IR) Data


OBJECTIVE: Develop an 8x compression algorithm for space infrared data. DESCRIPTION: While Infrared (IR) space surveillance data is typically massive, it must reach Warfighters in the field via a very narrow (56k) communication channel. By implementing 8x data compression algorithms it is anticipated that a larger Warfighter audience can be reached. Additionally, more data could be delivered via the downlink while simultaneously reducing the required bandwidth loads on the core Air Force network and Communication assets. This solicitation seeks an innovative 8x compression algorithm for space IR data which exceeds the standard Rice algorithm compression ratio [1]. We cannot afford to lose critical information to lossy compression; accordingly, we require a loss-less approach. It is also desirable that the compression algorithm not consume excessive amounts of processing power since it must be used on a satellite having stringent power and computer processing limitations. PHASE I: The Phase I work should include development of an efficient compression algorithm and representative software to demonstrate proven performance. There is no hardware requirement. PHASE II: The Phase II program should develop and deliver a turn-key source code that is in compliance with DoD regulations [2] for use in a DoD system. Shall include testing against real OPIR data for compression efficiency testing. PHASE III: Military Application: IR specific compression algorithms can be used for air or land based surveillance equipment by any DoD organization. Commercial Applications: IR specific compression algorithms can be used for air or land based surveillance equipment. REFERENCES: 1.Compression Algorithm for Infrared Hyperspectral Sounder Data. Irina Gladkova et al. NOAA/NESDIS, Washington, DC. Proceedings of the 2005 Data Compression Conference (DCC"05). 1068-0314/05 IEEE. 2. Procedures Manual for the Consultative Committee for Space Data Systems. INFORMATIONAL REPORT, CCSDS 120.0-G-2, GREEN BOOK, December 2006.
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