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Mathematical models for remote sensing image processing: models and methods for the analysis of 2D satellite and aerial images
This book maximizes reader insights into the field of mathematical models and methods for the processing of two-dimensional remote sensing images. It presents a broad analysis of the field, encompassing passive and active sensors, hyperrspectral images, synthetic aperture radar (SSAR), interferometric SAR, and polarimetric SAR data. At the same time , it address highly topical subjects involving remote sensing data types (e.g very high-resolution images, multiangular or multiresolution data, and satellite image time series) and analysis methodologies (e.g probabilistic graphical models, hirearchial image representations, kernel machines, data fusion, and compressive sensing) that currently have primary importance in the field of mathematical modelling for remote sensing data and/or on a specific methodological area, presenting both a through analysis of the previous literature and methodologicsl and experimental discussion of at least two advanced mathematical methods for information and advanced subjects are coverred. With each chapter being witten by research scientists from two different institutions, it offers multiple profesional experiences and perspective on each subject. The book also also providers expert analysis and commentary from leading remote sensing and image processing researchs, many of whom serve on the editorial boards of pestigious international jornal in these field, and are actively involved in international scienctifi societti. Providing the reader with a comphrehensive picture og the overall advances and the curresnt cutting-edge developments in the field of mathenatical models for remote sensing iamge alaysis, this book is ideal as both a referenscy reosurce and a textbook for graduate and doctoral students as well as for remote sensing scientiscts and practitioner.
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