Signal Theory Methods in Multispectral Remote Sensing

David A Landgrebe

ISBN 10: 047142028X / ISBN 13: 9780471420286

Published by John Wiley and Sons Ltd, 2003

About this Item

Remote sensing is used in aeronautics, global positioning, tracking, environmental, and meteorlogical applications. This book focusses on the fundamentals of the analysis of multispectral and hyperspectral image data from the point of view of signal processing engineering. Num Pages: 520 pages, index. BIC Classification: TTB; UYS. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 238 x 164 x 33. Weight in Grams: 917. . 2003. Hardcover. . . . . Seller Inventory # V9780471420286

Bibliographic Details

Title: Signal Theory Methods in Multispectral ...

Publisher: John Wiley and Sons Ltd

Publication Date: 2003

Binding: Hardcover

Condition: New

About this title

Synopsis:

An outgrowth of the author's extensive experience teaching senior and graduate level students, this is both a thorough introduction and a solid professional reference. Material covered has been developed based on a 35-year research program associated with such systems as the Landsat satellite program and later satellite and aircraft programs. This book covers existing aircraft and satellite programs, and several future programs.

From the Back Cover:

Practical methods for the optimal analysis of multispectral and hyperspectral image data

The field of remote sensing is a cross-disciplinary one, involving professionals ranging from signal processing engineers to earth science researchers to private and public sector practitioners, in nearly every region of the globe. The Signal Theory Approach offers powerful methods for analyzing the complex data involved in this field-methods which may not be familiar to many in non-engineering fields. In contrast to previous broad surveys of the subject, Signal Theory Methods in Multispectral Remote Sensing focuses on the practical knowledge data users of all types must have to optimally analyze multispectral and hyperspectral image data.

Both a textbook and self-teaching reference for professionals in the field, this book covers the fundamentals of the analysis of multispectral and hyperspectral image data from the point of view of signal processing engineering. Avoiding topics common to general treatments of remote sensing but not germane to practical applications, it offers concise discussions of:

• Pattern recognition methods as applied to the analysis of multivariate remotely sensed data
• The scene and sensor parts of a passive optical remote sensing system
• The statistical approach, including first-and second-order decision boundaries, error estimation, feature selection, and clustering
• Spectral feature design, the incorporation of spatial variations, noise in remote sensing systems, and other methods necessary for hyperspectral analysis

As hyperspectral data becomes more widely available, the need for practical ways to analyze the very large volume of hyperspectral data on a personal computer makes this an extremely timely and useful reference for all professionals and researchers involved in remote sensing.