Special Section on Onboard Compression and Processing for Space Data Systems

Reconfigurable architecture for real-time image compression on-board satellites

[+] Author Affiliations
Kristian Manthey, David Krutz

German Aerospace Center (DLR), Institute of Optical Sensor Systems, Optical Sensors and Electronics, Rutherfordstraße 2, 12489 Berlin, Germany

Ben Juurlink

Technische Universität Berlin, Embedded Systems Architecture, Einsteinufer 17, 10587 Berlin, Germany

J. Appl. Remote Sens. 9(1), 097497 (Jun 09, 2015). doi:10.1117/1.JRS.9.097497
History: Received December 15, 2014; Accepted May 12, 2015
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Abstract.  A high-speed image compression architecture with region-of-interest (ROI) support and with flexible access to compressed data based on the Consultative Committee for Space Data Systems 122.0-B-1 image data compression standard is presented. Modifications of the standard permit a change of compression parameters and the reorganization of the bit stream after compression. An additional index of the compressed data is created, which renders it possible to locate individual parts of the bit stream. On request, stored images can be reassembled according to the application’s needs and as requested by the ground station. Interactive transmission of the compressed data is possible such that overview images can be transmitted first followed by detailed information for the ROI. The architecture was implemented for a Xilinx Virtex-5QV and a single instance is able to compress images at a rate of 200Mpx/s at a clock frequency of 100 MHz. The design ensures that all parts of the system have a high utilization and parallelism. A Virtex-5QV allows compression of images with a width of up to 4096 px without external memory. The power consumption of the architecture is 4W. This example is one of the fastest implementations yet reported and sufficient for future high-resolution imaging systems.

© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Kristian Manthey ; David Krutz and Ben Juurlink
"Reconfigurable architecture for real-time image compression on-board satellites", J. Appl. Remote Sens. 9(1), 097497 (Jun 09, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.097497


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