Paper
18 August 2005 Effect of anomalies on data compression onboard a hyperspectral satellite
Author Affiliations +
Abstract
The Canadian Space Agency (CSA) is developing a pre-operational spaceborne Hyperspectral Environment and Resource Observer (HERO). HERO will be a Canadian optical Earth observation mission that will address the stewardship of natural resources for sustainable development within Canada and globally. To deal with the challenge of extremely high data rate and the huge data volume generated onboard, CSA has developed two near lossless data compression techniques for use onboard a satellite. CSA is planning to place a data compressor onboard HERO using these techniques to reduce the requirement for onboard storage and to better match the available downlink capacity. Anomalies in the raw hyperspectral data can be caused by detector and instrument defects. This work focuses on anomalies that are caused by dead detector elements, frozen detector elements, overresponsive detector elements and saturation. This paper addresses the effect of these anomalies in raw hyperspectral imagery on data compression. The outcome of this work will help to decide whether or not an onboard data preprocessing to remove these anomalies is required before compression. Hyperspectral datacubes acquired using two hyperspectral sensors were tested. Statistical measures were used to evaluate the data compression performance with or without removing the anomalies. The effect of anomalies on compressed data was also evaluated using a remote sensing application.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shen-En Qian, Martin Bergeron, Josee Levesque, and Allan Hollinger "Effect of anomalies on data compression onboard a hyperspectral satellite", Proc. SPIE 5889, Satellite Data Compression, Communications, and Archiving, 588902 (18 August 2005); https://doi.org/10.1117/12.613195
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Sensors

Detector arrays

Data compression

Signal to noise ratio

Remote sensing

Hyperspectral imaging

Target detection

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