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Mathematical Models For Remote Sensing Image Processing


Mathematical Models For Remote Sensing Image Processing
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Mathematical Models For Remote Sensing Image Processing


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.



Statistical Image Processing And Multidimensional Modeling


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.



Medical Image Processing


Medical Image Processing
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Author : Satya Prakash Yadav
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-09-23

Medical Image Processing written by Satya Prakash Yadav and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-23 with Science categories.


The goal of this book is to facilitate and stimulate cross-disciplinary research in the emerging paradigm of Medical Imaging. Especially this book is to focus on analysing and articulating proven and potential security measures to tightly secure Medical Image applications and services, which are being hosted and delivered through cloud infrastructures and platforms. This book will illustrate the prominent advancements in image processing and how intelligent image-processing techniques can be developed and deployed in the industrial market and for academicians. The readers will get to know all the right and relevant details to be empowered to successfully contribute to their personal and professional growth. The main focus of this book is to bring all the related technologies, novel findings, and managerial applications of Medical Imaging on a single platform to provide great readability, easy understanding, and smooth adaptability of various basic and advanced concepts to Researchers in Medical Engineers, Machine Learning and Data Analysis.



Land Cover Classification Of Remotely Sensed Images


Land Cover Classification Of Remotely Sensed Images
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Author : S. Jenicka
language : en
Publisher: Springer Nature
Release Date : 2021-03-10

Land Cover Classification Of Remotely Sensed Images written by S. Jenicka and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-10 with Technology & Engineering categories.


The book introduces two domains namely Remote Sensing and Digital Image Processing. It discusses remote sensing, texture, classifiers, and procedures for performing the texture-based segmentation and land cover classification. The first chapter discusses the important terminologies in remote sensing, basics of land cover classification, types of remotely sensed images and their characteristics. The second chapter introduces the texture and a detailed literature survey citing papers related to texture analysis and image processing. The third chapter describes basic texture models for gray level images and multivariate texture models for color or remotely sensed images with relevant Matlab source codes. The fourth chapter focuses on texture-based classification and texture-based segmentation. The Matlab source codes for performing supervised texture based segmentation using basic texture models and minimum distance classifier are listed. The fifth chapter describes supervised and unsupervised classifiers. The experimental results obtained using a basic texture model (Uniform Local Binary Pattern) with the classifiers described earlier are discussed through the relevant Matlab source codes. The sixth chapter describes land cover classification procedure using multivariate (statistical and spectral) texture models and minimum distance classifier with Matlab source codes. A few performance metrics are also explained. The seventh chapter explains how texture based segmentation and land cover classification are performed using the hidden Markov model with relevant Matlab source codes. The eighth chapter gives an overview of spatial data analysis and other existing land cover classification methods. The ninth chapter addresses the research issues and challenges associated with land cover classification using textural approaches. This book is useful for undergraduates in Computer Science and Civil Engineering and postgraduates who plan to do research or project work in digital image processing. The book can serve as a guide to those who narrow down their research to processing remotely sensed images. It addresses a wide range of texture models and classifiers. The book not only guides but aids the reader in implementing the concepts through the Matlab source codes listed. In short, the book will be a valuable resource for growing academicians to gain expertise in their area of specialization and students who aim at gaining in-depth knowledge through practical implementations. The exercises given under texture based segmentation (excluding land cover classification exercises) can serve as lab exercises for the undergraduate students who learn texture based image processing.



Remote Sensing Image Processing Algorithms For Detecting Air Turbulence Patterns


Remote Sensing Image Processing Algorithms For Detecting Air Turbulence Patterns
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Author : Maged Marghany
language : en
Publisher: CRC Press
Release Date : 2024-11-22

Remote Sensing Image Processing Algorithms For Detecting Air Turbulence Patterns written by Maged Marghany and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-22 with Technology & Engineering categories.


Injuries due to air turbulence has increased recently, therefore there is considerable concern and interest in understanding and detecting it more accurately. Presently hardly any research deals with air turbulence detection using remote sensing images. Most works use conventional optical remote sensing data with classical methods such as a library spectral signature, band ratio, and principal component analysis without designating new methods and technology. Very little research has attempted to implement optical and microwave remote sensing images for air turbulence detections. This book provides new image processing procedures for air turbulence detection using advanced remote sensing images and quantum image processing. Currently, there is a huge gap between research work in the field of air turbulence detection and advanced remote sensing technology. Most of the theories are not operated in terms of software modules. Most of the software packages in the field of remote sensing images cannot deal with advanced image processing techniques in air turbulence detections due to heavy mathematics work. In this view, this book fills a gap between advanced remote sensing technology and air turbulence detection. For instance, quantum image processing with a new generation of remote sensing technology such as RADARSAT-2 SAR images is also implemented to provide accurate air turbulence detections.



Environmental Management And Governance


Environmental Management And Governance
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Author : Charles W. Finkl
language : en
Publisher: Springer
Release Date : 2014-09-16

Environmental Management And Governance written by Charles W. Finkl and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-16 with Science categories.


This book deals with recent advances in coastal marine environmental management and governance. Various chapters consider new aspects of conservation, assessment of ecosystem health status, environmental survey and protection, frameworks of ocean service and governance, new applications of geo processing and GIS technology, beach management, aquaculture site selection, assessment of water quality (brine disposal and temperature dispersion from nuclear power plants), exploration and management of coastal karst, changing perceptions of dune management, advances in interpretation of sea-level indicators and real time environmental monitoring. New advances in both environmental management and governance are of the utmost importance for sustaining critical coastal marine areas. Offering such a diverse collection of works from coastal scientists around the world, who discuss many techniques and methods at the forefront of management and governance, this publication will be of interest to coastal researchers, coastal zone managers and regulatory agency personnel.



Handbook Of Research On Mathematical Modeling For Smart Healthcare Systems


Handbook Of Research On Mathematical Modeling For Smart Healthcare Systems
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Author : Samanta, Debabrata
language : en
Publisher: IGI Global
Release Date : 2022-06-24

Handbook Of Research On Mathematical Modeling For Smart Healthcare Systems written by Samanta, Debabrata and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-24 with Computers categories.


Advances in healthcare technologies have offered real-time guidance and technical assistance for diagnosis, monitoring, operation, and interventions. The development of artificial intelligence, machine learning, internet of things technology, and smart computing techniques are crucial in today’s healthcare environment as they provide frictionless and transparent financial transactions and improve the overall healthcare experience. This, in turn, has far-reaching effects on economic, psychological, educational, and organizational improvements in the way we work, teach, learn, and provide care. These advances must be studied further in order to ensure they are adapted and utilized appropriately. The Handbook of Research on Mathematical Modeling for Smart Healthcare Systems presents the latest research findings, ideas, innovations, developments, and applications in the field of modeling for healthcare systems. Furthermore, it presents the application of innovative techniques to complex problems in the case of healthcare. Covering a range of topics such as artificial intelligence, deep learning, and personalized healthcare services, this reference work is crucial for engineers, healthcare professionals, researchers, academicians, scholars, practitioners, instructors, and students.



Math Physics Foundation Of Advanced Remote Sensing Digital Image Processing


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.



Optical Remote Sensing Of Land Surface


Optical Remote Sensing Of Land Surface
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Author : Nicolas Baghdadi
language : en
Publisher: Elsevier
Release Date : 2016-09-13

Optical Remote Sensing Of Land Surface written by Nicolas Baghdadi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-13 with Technology & Engineering categories.


The considerable progress in instrumentation and in the development of methods for the processing and analysis of data places remote sensing at the center of various international programs for the surveillance and tracking of climatic and anthropogenic changes and effects on the environment. This volume presents optical imaging and LiDAR systems: their instrumentation, physics of measurement, processing methods and data analysis. The estimation of a digital terrain model based on optical images and LiDAR data is also discussed.This book, part of a set of six volumes, has been produced by scientists who are internationally renowned in their fields. It is addressed to students (engineers, Masters, PhD), engineers and scientists, specialists in Earth observation techniques and imaging systems.Through this pedagogical work, the authors contribute to breaking down the barriers that hinder the use of Earth observation data. - Provides clear and concise descriptions of modern remote sensing methods - Explores the most current remote sensing techniques with physical aspects of the measurement (theory) and their applications - Provides chapters on physical principles, measurement, and data processing for each technique described - Describes optical remote sensing technology, including a description of acquisition systems and measurement corrections to be made



Computational Intelligence And Intelligent Systems


Computational Intelligence And Intelligent Systems
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Author : Zhenhua Li
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-10-05

Computational Intelligence And Intelligent Systems written by Zhenhua Li 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 2009-10-05 with Computers categories.


Volumes CCIS 51 and LNCS 5812 constitute the proceedings of the Fourth Interational Symposium on Intelligence Computation and Applications, ISICA 2009, held in Huangshi, China, during October 23-25. ISICA 2009 attracted over 300 submissions. Through rigorous reviews, 58 papers were included in LNCS 5821,and 54 papers were collected in CCIS 51. ISICA conferences are one of the first series of international conferences on computational intelligence that combine elements of learning, adaptation, evolution and fuzzy logic to create programs as alternative solutions to artificial intelligence.