Multispectral Image Analysis Using the Object-Oriented Paradigm

Name: Multispectral Image Analysis Using the Object-Oriented Paradigm
Brand: Taylor & Francis Inc
Price: 211.75 AUD
Availability: BackOrder

By: Kumar Navulur

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Hardcover | 5 December 2006 | Edition Number 1

At a Glance

Hardcover
204 Pages

Dimensions(cm)
23.6 x 15.7 x 1.7

Hardcover

RRP $242.00

$211.75

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Bringing a fresh new perspective to remote sensing, object-based image analysis is a paradigm shift from the traditional pixel-based approach. Featuring various practical examples to provide understanding of this new modus operandi, Multispectral Image Analysis Using the Object-Oriented Paradigm reviews the current image analysis methods and demonstrates advantages to improve information extraction from imagery.

This reference describes traditional image analysis techniques, introduces object-oriented technology, and discusses the benefits of object-based versus pixel-based classification. It examines the creation of object primitives using image segmentation approaches and the use of various techniques for object classification. The author covers image enhancement methods, how to use ancillary data to constrain image segmentation, and concepts of semantic grouping of objects. He concludes by addressing accuracy assessment approaches. The accompanying downloadable resources present sample data that enable the use of different approaches to problem solving.

Integrating remote sensing techniques and GIS analysis, Multispectral Image Analysis Using the Object-Oriented Paradigm distills new tools to extract information from remotely sensed data.

Industry Reviews

". . . Navulur's book makes a valuable contribution because it offers a well-organized reference to contemporary developments in object-oriented image analysis, along with various creative ideas for implementation of these methods in practical solutions."

- Matthew Ramspott, Department of Geography, Frostburg State University, in Photogrammetric Engineering & Remote Sensing, September 2007, Vol. 73, No. 9

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