Object-Based Image Understanding of Remotely Sensed Imageries
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With the advances in space-borne imaging sensor technology, the potential for building geospatial databases has increased immensely; yet extracting the target information from the high resolution remote sensing image is still a challenging problem. This book discusses high degree of automation for processing, analysis and interpretation in handling complex information systems for recognizing and extracting the features of interest from high resolution remotely sensed imageries. Image segmentation and classification techniques are the main tools used for analyzing and understanding remotely sen...
With the advances in space-borne imaging sensor technology, the potential for building geospatial databases has increased immensely; yet extracting the target information from the high resolution remote sensing image is still a challenging problem. This book discusses high degree of automation for processing, analysis and interpretation in handling complex information systems for recognizing and extracting the features of interest from high resolution remotely sensed imageries. Image segmentation and classification techniques are the main tools used for analyzing and understanding remotely sensed imageries, which are discussed in detail. In most cases, important information for the understanding of an image is not represented in single pixels but in meaningful image objects. The image objects include the association of multiple pixels and their mutual relations, and hence object-based methodology has become one of the most important used strategies for the processing of remotely sensed images.
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