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Justsoso

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[资源] 【分享】[Springer 2005] Hyperspectral Data Compression

Hyperspectral Data Compression
Springer-Verlag, 2005
(425 pages, 6" x 9", hard-bound)
ISBN: 0-387-28579-2

Giovanni Motta, Francesco Rizzo, James A. Storer, Editors

This book provides a survey of recent results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery. Remote sensed data present special challenges in the acquisition, transmission, analysis, and storage process. Perhaps most significant is the information extraction process. In most cases accurate analysis depends on high quality data, which comes with a price tag: increased data volume. For example, the NASA JPL's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS, http://aviris.jpl.nasa.gov) records the visible and the near infrared spectrum of the reflected light of an area 2 to 12 kilometers wide and several kilometers long (depending on the duration of the flight) into hundreds of non overlapping bands. The resulting data volume typically exceeds 500 Megabytes per flight and it is mainly used for geological mapping, target recognition, and anomaly detection. On the other hand, ultraspectral sounders such as the NASA JPL's Atmospheric Infrared Sounder (AIRS, http://www airs.jpl.nasa.gov), which has recently become a reference in compression studies on this class of data, records thousands of bands covering the infrared spectrum and generates more than 12 Gigabytes of data daily.

Chapter 1 addresses compression architecture and reviews and compares compression methods.

Chapter 2 through 4 focus on lossless compression (where the decompressed image must be bit for bit identical to the original).

Chapter 5 (contributed by the editors) describes a lossless algorithm based on vector quantization with extensions to near lossless and possibly lossy compression for efficient browsing and pure pixel classification.

Chapters 6 deals with near lossless compression while Chapter 7 considers lossy techniques constrained by almost perfect classification.

Chapters 8 through 12 address lossy compression of hyperspectral imagery, where there is a tradeoff between compression achieved and the quality of the decompressed image.

Chapter 13 examines artifacts that can arise from lossy compression.

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[ Last edited by cadick on 2009-12-14 at 01:30 ]

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