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Hyperspectral Data Compression. 1st ed. Softcover of orig. ed. 2006
・ISBN 978-1-4419-3943-2 paper EUR 149.99
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★★★
| 著者・編者 | Motta, Giovanni / Rizzo, Francesco / Storer, James A. (eds.), |
|---|---|
| 出版社 | (Springer-Verlag New York Inc., US) |
| 出版年月 | 2010 |
| ページ数 | 418 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A05-56413＞ |
解説
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.