Evaluation of algorithms for compressing hyperspectral data

Sid Cook; Joseph C. Harsanyi; Vance Faber

doi:10.1117/12.512314

2 February 2004 Evaluation of algorithms for compressing hyperspectral data

Sid Cook, Joseph C. Harsanyi, Vance Faber

Proceedings Volume 5234, Sensors, Systems, and Next-Generation Satellites VII; (2004) https://doi.org/10.1117/12.512314
Event: Remote Sensing, 2003, Barcelona, Spain

Abstract

With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.

Citation Download Citation

Sid Cook, Joseph C. Harsanyi, and Vance Faber "Evaluation of algorithms for compressing hyperspectral data", Proc. SPIE 5234, Sensors, Systems, and Next-Generation Satellites VII, (2 February 2004); https://doi.org/10.1117/12.512314

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