Details

Autor(en) / Beteiligte

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

Titel

Hyperspectral Data Compression

Auflage

1. Aufl.

Ort / Verlag

New York, NY: Springer Science + Business Media

Erscheinungsjahr

2006

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• 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.