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Remote sensing, models, and methods for image processing /

This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms. Written from the viewpoint that i...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Schowengerdt, Robert A.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: San Diego : Academic Press, �1997.
Edición:2nd ed.
Temas:
Acceso en línea:Texto completo
Descripción
Sumario:This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms. Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, spatial, and geometric models are used to introduce advanced image processing techniques such as hyperspectral image analysis, fusion of multisensor images, and digital elevationmodel extraction from stereo imagery. The material is suited for graduate level engineering, physical and natural science courses, or practicing remote sensing scientists. Each chapter is enhanced by student exercises designed to stimulate an understanding of the material. Over 300 figuresare produced specifically for this book, and numerous tables provide a rich bibliography of the research literature.
Notas:Revised edition of: Techniques for image processing and classification in remote sensing.
Descripción Física:1 online resource (xlv, 522 pages) : illustrations (some color)
Bibliografía:Includes bibliographical references (pages 483-516) and index.