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Item Details
| Title:
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HYPERSPECTRAL DATA COMPRESSION
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| By: |
Giovanni Motta (Editor), Francesco Rizzo (Editor), James A. Storer (Editor) |
| Format: |
Hardback |
| List price:
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£139.99 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
0387285792 |
| ISBN 13: |
9780387285795 |
| Publisher: |
SPRINGER-VERLAG NEW YORK INC. |
| Pub. date: |
1 November, 2005 |
| Pages: |
418 |
| Description: |
Provides a survey of results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery. This work covers topics such as compression architecture, lossless compression, lossy techniques, and more. It also describes a lossless algorithm based on vector quantization. |
| Synopsis: |
Hyperspectral Data Compression provides a survey of recent results in the field of compression of remote sensed 3D data, with a particular interest in hyperspectral imagery. Chapter 1 addresses compression architecture, and reviews and compares compression methods. Chapters 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 browning and pure pixel classification. Chapter 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. |
| Illustrations: |
XII, 418 p. |
| Publication: |
US |
| Imprint: |
Springer-Verlag New York Inc. |
| Returns: |
Returnable |
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