The implementation of a lossless data compression module in an advanced orbiting system: Analysis and development

Data compression has been proposed for several flight missions as a means of either reducing on board mass data storage, increasing science data return through a bandwidth constrained channel, reducing TDRSS access time, or easing ground archival mass storage requirement. Several issues arise with the implementation of this technology. These include the requirement of a clean channel, onboard smoothing buffer, onboard processing hardware and on the algorithm itself, the adaptability to scene changes and maybe even versatility to the various mission types. This paper gives an overview of an ongoing effort being performed at Goddard Space Flight Center for implementing a lossless data compression scheme for space flight. We will provide analysis results on several data systems issues, the performance of the selected lossless compression scheme, the status of the hardware processor and current development plan

The development of lossless data compression technology for remote sensing applications

Lossless data compression has been studied for many NASA missions to achieve the benefit of increased science return, reduced onboard memory requirement, station contact time and communication bandwidth. This paper first addresses the requirement for onboard applications and provides rational for the selection of the Rice algorithm among other available techniques. A top-level description of the Rice algorithm will be given, along with some new capabilities already implemented in both software and hardware VLSI forms. The paper then addresses systems issues important for onboard implementation including sensor calibration, error propagation and data packetization. The latter part of the paper provides several case study examples drawn from a broad spectrum of science instruments including the thematic mapper, x-ray telescope, gamma-ray spectrometer, and acousto-optical spectrometer

End-to-end communication test on variable length packet structures utilizing AOS testbed

This paper describes a communication test, which successfully demonstrated the transfer of losslessly compressed images in an end-to-end system. These compressed images were first formatted into variable length Consultative Committee for Space Data Systems (CCSDS) packets in the Advanced Orbiting System Testbed (AOST). The CCSDS data Structures were transferred from the AOST to the Radio Frequency Simulations Operations Center (RFSOC), via a fiber optic link, where data was then transmitted through the Tracking and Data Relay Satellite System (TDRSS). The received data acquired at the White Sands Complex (WSC) was transferred back to the AOST where the data was captured and decompressed back to the original images. This paper describes the compression algorithm, the AOST configuration, key flight components, data formats, and the communication link characteristics and test results

A Hardware Architecture of a Counter-Based Entropy Coder

This paper describes a hardware architectural design of a real-time counter based entropy coder at a register transfer level (RTL) computing model. The architecture is based on a lossless compression algorithm called Rice coding, which is optimal for an entropy range of bits per sample. The architecture incorporates a word-splitting scheme to extend the entropy coverage into a range of bits per sample. We have designed a data structure in a form of independent code blocks, allowing more robust compressed bitstream. The design focuses on an RTL computing model and architecture, utilizing 8-bit buffers, adders, registers, loader-shifters, select-logics, down-counters, up-counters, and multiplexers. We have validated the architecture (both the encoder and the decoder) in a coprocessor for 8 bits/sample data on an FPGA Xilinx XC4005, utilizing 61% of F&G-CLBs, 34% H-CLBs, 32% FF-CLBs, and 68% IO resources. On this FPGA implementation, the encoder and decoder can achieve 1.74 Mbits/s and 2.91 Mbits/s throughputs, respectively. The architecture allows pipelining, resulting in potentially maximum encoding throughput of 200 Mbit/s on typical real-time TTL implementations. In addition, it uses a minimum number of register elements. As a result, this architecture can result in low cost, low energy consumption and reduced silicon area realizations

Paper Session III-A - Data Compression and Error-Protection Coding

Data Compression and Error-protection coding are two of the now widely heard but not well understood terms associated with the Information Super Highway. But this was not always so. Their familiarity is a consequence of developments which were initiated nearly 50 years ago with the introduction of modern information theory by Claude Shannon. Both concepts and techniques which can dramatically improve the representation, storage and communication of digital data - the underlying component of modern information systems. Although often invisible to individual users, the commercial applications of compression and coding, which affect Our daily lives now, have become extremely broad. Few of these applications can claim they were not directly or indirectly influenced by prior investments in this technology by NASA and the military. This paper describes important specific ongoing NASA direct technology transfers of data compression and error-protection coding techniques/technology. First jointly used to improve the return of Voyager images from Uranus and Neptune by a factor of 4, these techniques and their NASA sponsored custom high-speed microcircuits are now independently enjoying widespread use. A simplified laymen\u27s description of these techniques and their performance characteristics is followed by a status on their technology transfer

Lossless Compression of Grayscale Digital Image Based on Two-Dimensional Differential Prediction Algorithm

Rice algorithm, which has been recommended by Consultative Committee for Space Data System (CCSDS) for space telescope image lossless compression, is studied. Due to the similarity, this algorithm is applied on lossless compression of X-ray digital image after improvement and a satisfying compression rate is obtained. Firstly, the algorithm process is presented. Later on, the compression and decompression algorithms are implemented on PE's X-ray machine GECCO2505 and the flat panel detector PAXSCAN2520. Finally, the status of the technology is presented with its performance in X-ray digital image compression and decompression applications

Application guide for universal source encoding for space

Lossless data compression was studied for many NASA missions. The Rice algorithm was demonstrated to provide better performance than other available techniques on most scientific data. A top-level description of the Rice algorithm is first given, along with some new capabilities implemented in both software and hardware forms. Systems issues important for onboard implementation, including sensor calibration, error propagation, and data packetization, are addressed. The latter part of the guide provides twelve case study examples drawn from a broad spectrum of science instruments

1994 Science Information Management and Data Compression Workshop

This document is the proceedings from the 'Science Information Management and Data Compression Workshop,' which was held on September 26-27, 1994, at the NASA Goddard Space Flight Center, Greenbelt, Maryland. The Workshop explored promising computational approaches for handling the collection, ingestion, archival and retrieval of large quantities of data in future Earth and space science missions. It consisted of eleven presentations covering a range of information management and data compression approaches that are being or have been integrated into actual or prototypical Earth or space science data information systems, or that hold promise for such an application. The workshop was organized by James C. Tilton and Robert F. Cromp of the NASA Goddard Space Flight Center

The Space and Earth Science Data Compression Workshop

This document is the proceedings from a Space and Earth Science Data Compression Workshop, which was held on March 27, 1992, at the Snowbird Conference Center in Snowbird, Utah. This workshop was held in conjunction with the 1992 Data Compression Conference (DCC '92), which was held at the same location, March 24-26, 1992. The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The workshop consisted of eleven papers presented in four sessions. These papers describe research that is integrated into, or has the potential of being integrated into, a particular space and/or Earth science data information system. Presenters were encouraged to take into account the scientists's data requirements, and the constraints imposed by the data collection, transmission, distribution, and archival system