Space data compression standards

IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120)

A high performance lossy data compression technique is currently being developed for space science applications under the requirement of high-speed push-broom scanning. The technique is also error-resilient in that error propagation is contained within a few scan lines. The algorithm is based on block-transform combined with bit-plane encoding; this combination results in an embedded bit string with exactly the desirable compression rate. The lossy coder is described. The compression scheme performs well on a suite of test images typical of images from spacecraft instruments. Hardware implementations are in development; a functional chip set is expected by the end of 2000.

2003

Offer royalty free license to all CCSDS space agencies if any Process both frame and non-frame (push-broom) data patent is included in the algorithm Offer adjustable coded data rate or image quality (up to a lossless

spie.org

With the advances in contemporary active and passive sensor technologies with higher spectral and/or spatial resolutions and faster scanning speeds, more powerful airborne and spaceborne instruments.

The goal of the Science Information Management and Data Compression Workshop was to explore 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 fourteen 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. Papers were selected from papers submitted in response to a widely distributed Call for Papers. Fourteen papers were presented in 3 sessions. Discussion was encouraged by scheduling ample time for each paper. The workshop was organized by James C. Tilton and Robert F. Cromp of the NASA Goddard Space Flight Center.

2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2013

This paper examines the problem of of developing a lossless compression scheme for data from a nano-satellite being developed by the University of Saskatchewan Space Design team, the USST-Sat. The benefit of compressing scientific data from the satellite will be an increased ability to perform experiments and downlink the results. Goals for the compression scheme are to maximize space savings and result in a net energy savings over storing and transmitting uncompressed data. Our evaluations show that the custom scheme that we developed, called USST-Compress, performs compression as well as or better than the generic compression schemes evaluated, and additionally results in better net energy savings.

Journal of Applied Remote Sensing, 2010

With the advances in modern active and passive sensor technologies with higher spectral and spatial resolutions as well as faster scanning speeds, more powerful satellite instruments are being developed for remote sensing of the atmosphere, oceans, lands of the Earth, and other planets. These advanced technologies result in a significant increase in data volume. The explosion in the amount, size and dimensionality of current and future remote sensing data collected on a daily basis presents new challenges to satellites with limited access to an increasingly congested radio frequency spectrum. Data compression techniques provide useful tools for efficient and effective downlink and rebroadcast over a limited-bandwidth errorprone satellite channel. Considerable savings in data storage and transfer in satellite data centers can be also achieved using data compression methods. Various satellite data may have different data characteristics. Data compression methods which explore specific data characteristics may lead to better compression gains. Furthermore, data compression can be lossless or lossy, depending on available satellite bandwidths and mission requirements. Lossy compression needs an impact study to balance between data fidelity and scientific tolerance. The goals of this special section of the Journal of Applied Remote Sensing (JARS) are to explore stateof-the-art methods and techniques for compression, transmission, and storage of contemporary and future satellite remote sensing data. After an extensive peer review, one review paper [1] and thirteen research papers [2-14] were accepted for publication in the special section, covering various aspects of satellite data compression, including lossless or lossy compression of ultraspectral, hyperspectral and multispectral data, onboard compression chip development, onsite GPUaccelerated data compression, and error-correcting coding for satellite error-prone transmission. As guest editor, I would like to thank the authors for their contributions and the reviewers for their service. A brief synopsis of each accepted paper is provided below. Shen-En Qian [1] reviewed the research and developments in the last decade on near lossless satellite data compression techniques at the Canadian Space Agency (CSA). The hardware developments of two vector quantization-based near lossless hyperspectral data compression techniques were presented. Martin et al. [2] studied the impact of JPEG2000-based lossy compression of hyperspectral images on the quality of the endmembers extracted by three different

A robust noiseless encoding scheme is presented for encoding the gamma ray spectroscopy data. The encoding algorithm is simple to implement and has minimal buffering requirements. The decoder contains error correcting capability in the form of a MAP receiver. While the MAP receiver adds some complexity, this is limited to the decoder. Nothing additional is needed at the encoder side for its functioning.

IEEE Transactions on Geoscience and Remote Sensing, 1990

1993

CITATIONS 0 READS 15 4 authors, including:

1991

Soon after space and Earth science data is collected, it is stored in one or more archival facilities for later retrieval and analysis. Since the purpose of the archival process is to keep an accurate and complete record of data, any data compression used in an archival system must be lossless, and protect against propagation of error in the storage media.