Mathematical Models For Remote Sensing Image Processing
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Mathematical Models For Remote Sensing Image Processing
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Author : Gabriele Moser
language : en
Publisher: Springer
Release Date : 2017-11-28
Mathematical Models For Remote Sensing Image Processing written by Gabriele Moser and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-28 with Technology & Engineering categories.
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, hyperspectral images, synthetic aperture radar (SAR), interferometric SAR, and polarimetric SAR data. At the same time, it addresses 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, hierarchical image representations, kernel machines, data fusion, and compressive sensing) that currently have primary importance in the field of mathematical modelling for remote sensing and image processing. Each chapter focuses on a particular type of remote sensing data and/or on a specific methodological area, presenting both a thorough analysis of the previous literature and a methodological and experimental discussion of at least two advanced mathematical methods for information extraction from remote sensing data. This organization ensures that both tutorial information and advanced subjects are covered. With each chapter being written by research scientists from (at least) two different institutions, it offers multiple professional experiences and perspectives on each subject. The book also provides expert analysis and commentary from leading remote sensing and image processing researchers, many of whom serve on the editorial boards of prestigious international journals in these fields, and are actively involved in international scientific societies. Providing the reader with a comprehensive picture of the overall advances and the current cutting-edge developments in the field of mathematical models for remote sensing image analysis, this book is ideal as both a reference resource and a textbook for graduate and doctoral students as well as for remote sensing scientists and practitioners.
Image Analysis Classification And Change Detection In Remote Sensing
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Author : Morton John Canty
language : en
Publisher: CRC Press
Release Date : 2019-03-11
Image Analysis Classification And Change Detection In Remote Sensing written by Morton John Canty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-11 with Technology & Engineering categories.
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and it features a tight interweaving of statistical and machine learning theory of algorithms with computer codes. It develops statistical methods for the analysis of optical/infrared and synthetic aperture radar (SAR) imagery, including wavelet transformations, kernel methods for nonlinear classification, as well as an introduction to deep learning in the context of feed forward neural networks. New in the Fourth Edition: An in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series. The accompanying software consists of Python (open source) versions of all of the main image analysis algorithms. Presents easy, platform-independent software installation methods (Docker containerization). Utilizes freely accessible imagery via the Google Earth Engine and provides many examples of cloud programming (Google Earth Engine API). Examines deep learning examples including TensorFlow and a sound introduction to neural networks, Based on the success and the reputation of the previous editions and compared to other textbooks in the market, Professor Canty’s fourth edition differs in the depth and sophistication of the material treated as well as in its consistent use of computer codes to illustrate the methods and algorithms discussed. It is self-contained and illustrated with many programming examples, all of which can be conveniently run in a web browser. Each chapter concludes with exercises complementing or extending the material in the text.
Image Analysis Classification And Change Detection In Remote Sensing
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Author : Morton J. Canty
language : en
Publisher: CRC Press
Release Date : 2014-06-06
Image Analysis Classification And Change Detection In Remote Sensing written by Morton J. Canty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-06 with Mathematics categories.
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python, Third Edition introduces techniques used in the processing of remote sensing digital imagery. It emphasizes the development and implementation of statistically motivated, data-driven techniques. The author achieves this by tightly interweaving theory, algorithms, and computer codes. See What’s New in the Third Edition: Inclusion of extensive code in Python, with a cloud computing example New material on synthetic aperture radar (SAR) data analysis New illustrations in all chapters Extended theoretical development The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power. The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.
Image Processing For Remote Sensing
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Author : C.H. Chen
language : en
Publisher: CRC Press
Release Date : 2007-10-17
Image Processing For Remote Sensing written by C.H. Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-17 with Technology & Engineering categories.
Edited by leaders in the field, with contributions by a panel of experts, Image Processing for Remote Sensing explores new and unconventional mathematics methods. The coverage includes the physics and mathematical algorithms of SAR images, a comprehensive treatment of MRF-based remote sensing image classification, statistical approaches for
Statistical Image Processing And Multidimensional Modeling
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Author : Paul Fieguth
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-10-17
Statistical Image Processing And Multidimensional Modeling written by Paul Fieguth and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-17 with Mathematics categories.
Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something—an artery, a road, a DNA marker, an oil spill—from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over a two or higher dimensional space, and to which standard image-processing algorithms may not apply. There are many important data analysis methods developed in this text for such statistical image problems. Examples abound throughout remote sensing (satellite data mapping, data assimilation, climate-change studies, land use), medical imaging (organ segmentation, anomaly detection), computer vision (image classification, segmentation), and other 2D/3D problems (biological imaging, porous media). The goal, then, of this text is to address methods for solving multidimensional statistical problems. The text strikes a balance between mathematics and theory on the one hand, versus applications and algorithms on the other, by deliberately developing the basic theory (Part I), the mathematical modeling (Part II), and the algorithmic and numerical methods (Part III) of solving a given problem. The particular emphases of the book include inverse problems, multidimensional modeling, random fields, and hierarchical methods.
Image Processing Ii
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Author : Martin J. Turner
language : en
Publisher: Woodhead Publishing Limited
Release Date : 2000
Image Processing Ii written by Martin J. Turner and has been published by Woodhead Publishing Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.
This work presents an up-to-date record of international research on image restoration on the interaction of image processing as it relates to mathematical modelling. It covers in great detail its reconstruction and restoration, image comprehension, fractals and wavelets, pattern recognition and image understanding. The level is appropriate for advanced study and advanced research for applied mathematicians, computer scientists, electrical and electro-mechanical engineers, and scientists working in IT, remote sensing, medical imaging, vision systems, spectroscopy, virtual reality, military technology, electro-optics, biochemistry and cartigraphy.
Deep Cognitive Modelling In Remote Sensing Image Processing
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Author :
language : en
Publisher:
Release Date : 2024
Deep Cognitive Modelling In Remote Sensing Image Processing written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
Image Analysis Classification And Change Detection In Remote Sensing
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Author : Morton John Canty
language : en
Publisher: CRC Press
Release Date : 2019
Image Analysis Classification And Change Detection In Remote Sensing written by Morton John Canty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Mathematics categories.
Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and it features a tight interweaving of statistical and machine learning theory of algorithms with computer codes. It develops statistical methods for the analysis of optical/infrared and synthetic aperture radar (SAR) imagery, including wavelet transformations, kernel methods for nonlinear classification, as well as an introduction to deep learning in the context of feed forward neural networks. New in the Fourth Edition: An in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series. The accompanying software consists of Python (open source) versions of all of the main image analysis algorithms. Presents easy, platform-independent software installation methods (Docker containerization). Utilizes freely accessible imagery via the Google Earth Engine and provides many examples of cloud programming (Google Earth Engine API). Examines deep learning examples including TensorFlow and a sound introduction to neural networks, Based on the success and the reputation of the previous editions and compared to other textbooks in the market, Professor Canty's fourth edition differs in the depth and sophistication of the material treated as well as in its consistent use of computer codes to illustrate the methods and algorithms discussed. It is self-contained and illustrated with many programming examples, all of which can be conveniently run in a web browser. Each chapter concludes with exercises complementing or extending the material in the text.
Image Analysis Classification And Change Detection In Remote Sensing
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Author : Morton J. Canty
language : en
Publisher: CRC Press
Release Date : 2011-03-05
Image Analysis Classification And Change Detection In Remote Sensing written by Morton J. Canty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-05 with Technology & Engineering categories.
Demonstrating the breadth and depth of growth in the field since the publication of the popular first edition, Image Analysis, Classification and Change Detection in Remote Sensing, with Algorithms for ENVI/IDL, Second Edition has been updated and expanded to keep pace with the latest versions of the ENVI software environment. Effectively interweaving theory, algorithms, and computer codes, the text supplies an accessible introduction to the techniques used in the processing of remotely sensed imagery. This significantly expanded edition presents numerous image analysis examples and algorithms, all illustrated in the array-oriented language IDL—allowing readers to plug the illustrations and applications covered in the text directly into the ENVI system—in a completely transparent fashion. Revised chapters on image arrays, linear algebra, and statistics convey the required foundation, while updated chapters detail kernel methods for principal component analysis, kernel-based clustering, and classification with support vector machines. Additions to this edition include: An introduction to mutual information and entropy Algorithms and code for image segmentation In-depth treatment of ensemble classification (adaptive boosting ) Improved IDL code for all ENVI extensions, with routines that can take advantage of the parallel computational power of modern graphics processors Code that runs on all versions of the ENVI/IDL software environment from ENVI 4.1 up to the present—available on the author's website Many new end-of-chapter exercises and programming projects With its numerous programming examples in IDL and many applications supporting ENVI, such as data fusion, statistical change detection, clustering and supervised classification with neural networks—all available as downloadable source code—this self-contained text is ideal for classroom use or self study.
Math Physics Foundation Of Advanced Remote Sensing Digital Image Processing
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Author : Lei Yan
language : en
Publisher: Springer Nature
Release Date : 2023-07-31
Math Physics Foundation Of Advanced Remote Sensing Digital Image Processing written by Lei Yan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-31 with Technology & Engineering categories.
This book focuses on the mathematical and physical foundations of remote sensing digital image processing and introduces key algorithms utilized in this area. The book fully introduces the basic mathematical and physical process of digital imaging, the basic theory and algorithm of pixel image processing, and the higher-order image processing algorithm and its application. This book skillfully and closely integrates theory, algorithms, and applications, making it simple for readers to understand and use. Researchers and students working in the fields of remote sensing, computer vision, geographic information science, electronic information, etc., can profit from this book. For their work and research in digital image processing, they can master the fundamentals of imaging and image processing techniques.