Warner H. Miller

A real time lossless data compression technology for remote-sensing and other 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 a rationale 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 status of the technology will be presented with its performance in several applications including remote sensing, medical imaging and seismology.

Visually lossless data compression technique for real-time frame/pushbroom space imagers

A visually lossless data compression technique is currently being developed for space science applications under the requirement of high-speed push-broom scanning. The technique is also applicable to frame based imaging data. The algorithm first performs a block transform of either a hybrid of modulated lapped transform (MLT) with discrete cosine transform (DCT), or a 2-dimensional MLT. The transform is followed by a bit-plane encoding; this results in an embedded bit string with exact desirable compression rate specified by the user. The approach requires no unique look-up table to maximize its performance and is error-resilient in that error propagation is contained within a few scan lines for push- broom applications. The compression scheme performs well on a suite of test images acquired from spacecraft instruments. Flight qualified hardware implementations are in development; a functional chip set is expected by the end of 2001. The chip set is being designed to compress data in excess of 20 Msamples/sec and support quantization from 2 to 16 bits.

A Seismic Signal Processor Suitable for Use with the NOAA/GOES Satellite Data Collection System

Because of the high data-rate requirements, a practical system capable of collecting seismic information in the field and relaying it, via satellite, to a central collection point is not yet available. A seismic signal processor has been developed and tested for use with the NOAA/ GOES satellite data collection system. Performance tests on recorded, as well as real time, short period signals indicate that the event recognition technique used is nearly perfect in its rejection of environmental noise and other non-seismic signals and that, with the use of solid state buffer memories, data can be acquired in many swarm situations. The design of a complete field data collection platform is discussed based on the prototype evaluation.

A real-time high performance data compression technique for space applications

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 applicable to frame based imaging and is error-resilient in that error propagation is contained within a few scan lines. The algorithm is based on a hybrid of modulated lapped transform (MLT) and discrete cosine transform (DCT) combined with bit-plane encoding; this combination results in an embedded bit string with exactly the desirable compression rate as desired by the user. The approach requires no unique table to maximize its performance. The compression scheme performs well on a suite of test images typical of images from spacecraft instruments. Flight qualified hardware implementations are in development; a functional chip set is expected by the end of 2001. The chip set is being designed to compress data in excess of 20 Msamples/sec and support quantizations from 2 to 16 bits.

Performance of an enhanced DCT compression system for space applications

A low bit-rate data compression system utilizing a hybrid transform has been implemented for space applications. This hybrid transform reduces blocking distortion inherent in a 2D DCT and has smaller distortion measurement. The system also employs a developed adaptive entropy coder to reduce overhead associated with Huffman code tables. The performance of the system will be given along with its comparison with a JPEG compression system.

On-Board Image Compression for the RAE Lunar Mission

The requirements, design, implementation, and flight performance of an on-board image compression system for the lunar orbiting Radio Astronomy Explorer-2 (RAE-2) spacecraft are described. The image to be compressed is a panoramic camera view of the long radio astronomy antenna booms used for gravity-gradient stabilization of the spacecraft. A compression ratio of 32 to 1 is obtained by a combination of scan line skipping and adaptive run-length coding. The compressed imagery data are convolutionally encoded for error protection. This image compression system occupies about 1000 cm2 and consumes 0.4 W.

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 is 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, acousto-optical spectrometer.<<ETX>>