Alejandro C. Frery - Böcker

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 visualizationComprehensive 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 modelPractical discussions of parameter estimations, including the Bernoulli distribution, the negative binomial distribution, and the uniform distributionIn-depth examinations of applications, including statistical filters and classificationPerfect 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 introduces the statistical software R to the image processing community in an intuitive and practical manner. R brings interesting statistical and graphical tools which are important and necessary for image processing techniques. Furthermore, it has been proved in the literature that R is among the most reliable, accurate and portable statistical software available. Both the theory and practice of R code concepts and techniques are presented and explained, and the reader is encouraged to try their own implementation to develop faster, optimized programs. Those who are new to the field of image processing and to R software will find this work a useful introduction. By reading the book alongside an active R session, the reader will experience an exciting journey of learning and programming.

Image processing is concerned with the analysis and manipulation of images by computer. Providing a thorough treatment of image processing with an emphasis on those aspects most used in computer graphics, the authors concentrate on describing and analyzing the underlying concepts rather than on presenting algorithms or pseudocode. As befits a modern introduction to this topic, a good balance is struck between discussing the underlying mathematics and the main topics: signal processing, data discretization, the theory of colour and different colour systems, operations in images, dithering and half-toning, warping and morphing and image processing.This second edition reflects recent trends in science andtechnology that exploit image processing in computer graphics and vision applications. Stochastic image models and statistical methods for image processing are covered as are: A modern approach and new developments in the area, Probability theory for image processing, Applications in image analysis and computer vision.

Image processing is concerned with the analysis and manipulation of images by computer. Providing a thorough treatment of image processing, with an emphasis on those aspects most used in computer graphics and vision, this fully revised second edition concentrates on describing and analyzing the underlying concepts of this subject. As befits a modern introduction to this topic, a good balance is struck between discussing the underlying mathematics and the main topics of signal processing, data discretization, the theory of color and different color systems, operations in images, dithering and half-toning, warping and morphing, and image processing. Significantly expanded and revised, this easy-to-follow text/reference reflects recent trends in science and technology that exploit image processing in computer graphics and vision applications. Stochastic image models and statistical methods for image processing are covered, as is probability theory for image processing, and a focus on applications in image analysis and computer vision.Features: / Includes 5 new chapters and major changes throughout / Adopts a conceptual approach with emphasis on the mathematical concepts and their applications /Introduces an abstraction paradigm that relates mathematical models with image processing techniques and implementation methods - used throughout to help understanding of the mathematical theory and its practical use / Motivates through an elementary presentation, opting for an intuitive description where needed / Contains adopted innovative formulations whenever necessary for clarity of exposition / Provides numerous examples and illustrations, as an aid to understanding / Focuses on the aspects of image processing that have importance in computer graphics and vision applications / Offers a comprehensive introductory chapter for instructors This comprehensive text imparts a good conceptual understanding of the topic, as a basis for further study, and is suitable both as a textbook and a professional reference.The current extended edition is a must-have resource and guide for all studying or interested in this field.

This book presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2024), organized by the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India, in June 2024.

The book explores the convergence of healthcare and cutting-edge technology, making it a captivating subject for readers interested in future research.