Synthetic aperture radar provides broad-area imaging at high resolutions, which is used in applications such as environmental monitoring, earth-resource mapping, and military systems. This book presents the tools required for the digital processing of synthetic aperture radar images. They are of three types: (a) the elements of physics, (b) mathematical models and (c) image processing methods adapted to particular applications.

This practical reference shows SAR system designers and remote sensing specialists how to produce higher quality SAR images using data-driven algorithms, and apply powerful new techniques to measure and analyze SAR image content.

This text brings together 18 papers that examine SAR image analysis, and its modelling and techniques

SAR IMAGE ANALYSIS — A COMPUTATIONAL STATISTICS APPROACH Discover how to use statistics to extract information from SAR imagery In SAR Image Analysis — A Computational Statistics Approach, an accomplished team of researchers delivers a practical exploration of how to use statistics to extract information from SAR imagery. The authors discuss various models, supply sample data and code, and explain theoretical aspects of SAR image analysis that are highly relevant to practitioners and students. The book offers the theoretical properties of models, estimators, interpretation, data visualization, and advanced techniques, along with the data and code samples, that students require to learn effectively and efficiently. SAR Image Analysis — A Computational Statistics Approach provides various exercises throughout the book to help readers reinforce and retain the extensive information on parameter estimation, applications, reproducibility, replicability, and advanced topics, like robust estimators and stochastic distances, contained within. The book also includes: Thorough introductions to data acquisition and the elements of data analysis and image processing with R, including useful R packages, preprocessing SAR data, and visualization Comprehensive explorations of intensity SAR data and the multiplicative model, including the (SAR) gamma distribution, the K distribution, the G0 distribution, and more general distributions under the multiplicative model Practical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distribution In-depth examinations of applications, including statistical filters and classification Perfect for undergraduate and graduate students studying remote sensing, data analysis, and statistics, SAR Image Analysis — A Computational Statistics Approach is also an indispensable resource for researchers, practitioners, and professionals seeking a one-stop resource on how to use statistics to extract information from SAR imagery.

This book constitutes the refereed proceedings of the International Conference on Advances in Information Technology and Mobile Communication, AIM 2011, held at Nagpur, India, in April 2011. The 31 revised full papers presented together with 27 short papers and 34 poster papers were carefully reviewed and selected from 313 submissions. The papers cover all current issues in theory, practices, and applications of Information Technology, Computer and Mobile Communication Technology and related topics.

Written for students, remote sensing specialists, researchers and SAR system designers, Processing of SAR Data shows how to produce quality SAR images. In particular, this practical reference presents new methods and algorithms concerning the interferometric processing of SAR data with emphasis on system and signal theory, namely how SAR imagery is formed, how interferometry SAR images are created, and a detailed mathematical description of different focussing algorithms. Starting with the processing basics and progressing to the final geo-coded SAR data product, the book describes the complete processing steps in detail. Algorithms based on the effects of side-looking geometry are developed to correct foreshortening, shadowing and layover.