Navulur, Kumar
Navulur, Kumar
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.
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.
Introduction. Multispectral Remote Sensing Sensors. Why an Object Oriented Approach? Creating Objects. Object-Based Image Analysis. Advanced Object Image Analysis. Accuracy Assessment References.
Featuring various hands-on examples to provide understanding of this new approach, Multispectral Image Analysis Using the Object-Oriented Paradigm shows how to extract information from remotely sensed data for applications in agriculture, visual simulation, civil government mapping, forestry, fire risk assessment, and more. This bo
". . . 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
Bringing a fresh perspective to remote sensing, object-based image analysis is a paradigm shift from the traditional pixel-based approach. This work reviews the image analysis methods and demonstrates advantages to improve information extraction from imagery.
Klappentext
Bringing a fresh perspective to remote sensing, object-based image analysis is a paradigm shift from the traditional pixel-based approach. This work reviews the image analysis methods and demonstrates advantages to improve information extraction from imagery.
