Remote Sensing Image Fusion Download Ebook PDF Epub Online

Author : Luciano Alparone
Bruno Aiazzi
Publisher : CRC Press
Release : 2019-12-22
Page : 342
Category :
ISBN 13 : 9780367868185
Description :


A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and panchromatic images, and fusion of data from heterogeneous sensors such as optical and synthetic aperture radar (SAR) images and integration of thermal and visible/near-infrared images. They also explore new trends of signal/image processing, such as compressive sensing and sparse signal representations. The book brings a new perspective to a multidisciplinary research field that is becoming increasingly articulate and comprehensive. It fosters signal/image processing methodologies toward the goal of information extraction, either by humans or by machines, from remotely sensed images. The authors explain how relatively simple processing methods tailored to the specific features of the images may be winning in terms of reliable performance over more complex algorithms based on mathematical theories and models unconstrained from the physical behaviors of the instruments. Ultimately, the book covers the births and developments of three generations of RS image fusion. Established textbooks are mainly concerned with the earliest generation of methods. This book focuses on second generation methods you can use now and new trends that may become third generation methods. Only the lessons learned with second generation methods will be capable of fostering the excellence among the myriad of methods that are proposed almost every day by the scientific literature.


Author : Christine Pohl
John van Genderen
Publisher : CRC Press
Release : 2016-10-03
Page : 266
Category : Technology & Engineering
ISBN 13 : 1315353067
Description :


Remote Sensing Image Fusion: A Practical Guide gives an introduction to remote sensing image fusion providing an overview on the sensors and applications. It describes data selection, application requirements and the choice of a suitable image fusion technique. It comprises a diverse selection of successful image fusion cases that are relevant to other users and other areas of interest around the world.?The book helps newcomers to obtain a quick start into the practical value and benefits of multi-sensor image fusion. Experts will find this book useful to obtain an overview on the state of the art and understand current constraints that need to be solved in future research efforts. For industry professionals the book can be a great introduction and basis to understand multisensor remote sensing image exploitation and the development of commercialized image fusion software from a practical perspective. The book concludes with a chapter on current trends and future developments in remote sensing image fusion. Along with the book, RSIF website provides additional up-to-date information in the field.


Author : Luciano Alparone
Bruno Aiazzi
Publisher : CRC Press
Release : 2015-03-06
Page : 342
Category : Science
ISBN 13 : 1466587504
Description :


A synthesis of more than ten years of experience, Remote Sensing Image Fusion covers methods specifically designed for remote sensing imagery. The authors supply a comprehensive classification system and rigorous mathematical description of advanced and state-of-the-art methods for pansharpening of multispectral images, fusion of hyperspectral and


Author : George Bebis
Bahram Parvin
Publisher : Springer Science & Business Media
Release : 2008-11-13
Page : 1203
Category : Computers
ISBN 13 : 3540896457
Description :


The two volume set LNCS 5358 and LNCS 5359 constitutes the refereed proceedings of the 4th International Symposium on Visual Computing, ISVC 2008, held in Las Vegas, NV, USA, in December 2008. The 102 revised full papers and 70 poster papers presented together with 56 full and 8 poster papers of 8 special tracks were carefully reviewed and selected from more than 340 submissions. The papers are organized in topical sections on computer graphics, visualization, shape/recognition, video analysis and event recognition, virtual reality, reconstruction, motion, face/gesture, and computer vision applications. The 8 additional special tracks address issues such as object recognition, real-time vision algorithm implementation and application, computational bioimaging and visualization, discrete and computational geometry, soft computing in image processing and computer vision, visualization and simulation on immersive display devices, analysis and visualization of biomedical visual data, as well as image analysis for remote sensing data.


Author : Tania Stathaki
Publisher : Elsevier
Release : 2011-08-29
Page : 520
Category : Computers
ISBN 13 : 9780080558523
Description :


The growth in the use of sensor technology has led to the demand for image fusion: signal processing techniques that can combine information received from different sensors into a single composite image in an efficient and reliable manner. This book brings together classical and modern algorithms and design architectures, demonstrating through applications how these can be implemented. Image Fusion: Algorithms and Applications provides a representative collection of the recent advances in research and development in the field of image fusion, demonstrating both spatial domain and transform domain fusion methods including Bayesian methods, statistical approaches, ICA and wavelet domain techniques. It also includes valuable material on image mosaics, remote sensing applications and performance evaluation. This book will be an invaluable resource to R&D engineers, academic researchers and system developers requiring the most up-to-date and complete information on image fusion algorithms, design architectures and applications. Combines theory and practice to create a unique point of reference Contains contributions from leading experts in this rapidly-developing field Demonstrates potential uses in military, medical and civilian areas


Author : Christine Pohl
John L. Van Genderen
Publisher : CRC Press
Release : 2017
Page : 266
Category : Computers
ISBN 13 : 9781315370101
Description :


Remote Sensing Image Fusion: A Practical Guidegives an introduction to remote sensing image fusion providing an overview on the sensors and applications. It describes data selection, application requirements and the choice of a suitable image fusion technique. It comprises a diverse selection of successful image fusion cases that are relevant to other users and other areas of interest around the world. The book helps newcomers to obtain a quick start into the practical value and benefits of multi-sensor image fusion. Experts will find this book useful to obtain an overview on the state of the art and understand current constraints that need to be solved in future research efforts. For industry professionals the book can be a great introduction and basis to understand multisensor remote sensing image exploitation and the development of commercialized image fusion software from a practical perspective. The book concludes with a chapter on current trends and future developments in remote sensing image fusion. Along with the book, RSIF website provides additional up-to-date information in the field. ture developments in remote sensing image fusion. Along with the book, RSIF website provides additional up-to-date information in the field.


Author : Manjunath V. Joshi
Kishor P. Upla
Publisher : Cambridge University Press
Release : 2019-01-31
Page : 300
Category : Computers
ISBN 13 : 1108475124
Description :


Written using clear and accessible language, this useful guide discusses fundamental concepts and practices of multi-resolution image fusion.


Author : Siddhartha Bhattacharyya
Hrishikesh Bhaumik
Publisher : Walter de Gruyter GmbH & Co KG
Release : 2018-12-17
Page : 193
Category : Computers
ISBN 13 : 3110550776
Description :


This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The possible challenges in this direction include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. Big data analytics is the process of examining large and varied data sets - i.e., big data - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. This volume is intended to be used as a reference by undergraduate and post graduate students of the disciplines of computer science, electronics and telecommunication, information science and electrical engineering. THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research fi ndings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the fi eld and create a broad knowledge about the most recent research.


Author :
Publisher :
Release : 2013
Page :
Category :
ISBN 13 : 9789535157144
Description :



Author : Arian Azarang
Nasser Kehtarnavaz
Publisher : Morgan & Claypool Publishers
Release : 2021-02-24
Page : 93
Category : Technology & Engineering
ISBN 13 : 1636390757
Description :


Image fusion in remote sensing or pansharpening involves fusing spatial (panchromatic) and spectral (multispectral) images that are captured by different sensors on satellites. This book addresses image fusion approaches for remote sensing applications. Both conventional and deep learning approaches are covered. First, the conventional approaches to image fusion in remote sensing are discussed. These approaches include component substitution, multi-resolution, and model-based algorithms. Then, the recently developed deep learning approaches involving single-objective and multi-objective loss functions are discussed. Experimental results are provided comparing conventional and deep learning approaches in terms of both low-resolution and full-resolution objective metrics that are commonly used in remote sensing. The book is concluded by stating anticipated future trends in pansharpening or image fusion in remote sensing.


Author : Rick S. Blum
Zheng Liu
Publisher : CRC Press
Release : 2018-10-03
Page : 528
Category : Technology & Engineering
ISBN 13 : 1420026984
Description :


Taking another lesson from nature, the latest advances in image processing technology seek to combine image data from several diverse types of sensors in order to obtain a more accurate view of the scene: very much the same as we rely on our five senses. Multi-Sensor Image Fusion and Its Applications is the first text dedicated to the theory and practice of the registration and fusion of image data, covering such approaches as statistical methods, color-related techniques, model-based methods, and visual information display strategies. After a review of state-of-the-art image fusion techniques, the book provides an overview of fusion algorithms and fusion performance evaluation. The following chapters explore recent progress and practical applications of the proposed techniques to solving problems in such areas as medical diagnosis, surveillance and biometric systems, remote sensing, nondestructive evaluation, blurred image restoration, and image quality assessment. Recognized leaders from industry and academia contribute the chapters, reflecting the latest research trends and providing useful algorithms to aid implementation. Supplying a 28-page full-color insert, Multi-Sensor Image Fusion and Its Applications clearly demonstrates the benefits and possibilities of this revolutionary development. It provides a solid knowledge base for applying these cutting-edge techniques to new challenges and creating future advances.


Author : Esra Tunc Gormus
Publisher :
Release : 2013
Page :
Category :
ISBN 13 :
Description :



Author : Gang Xiao
Durga Prasad Bavirisetti
Publisher : Springer Nature
Release : 2020-08-31
Page : 404
Category : Computers
ISBN 13 : 9811548676
Description :


This book systematically discusses the basic concepts, theories, research and latest trends in image fusion. It focuses on three image fusion categories – pixel, feature and decision – presenting various applications, such as medical imaging, remote sensing, night vision, robotics and autonomous vehicles. Further, it introduces readers to a new category: edge-preserving-based image fusion, and provides an overview of image fusion based on machine learning and deep learning. As such, it is a valuable resource for graduate students and scientists in the field of digital image processing and information fusion.


Author : Ni-Bin Chang
Kaixu Bai
Publisher : CRC Press
Release : 2018-02-21
Page : 528
Category : Technology & Engineering
ISBN 13 : 1351650637
Description :


Combining versatile data sets from multiple satellite sensors with advanced thematic information retrieval is a powerful way for studying complex earth systems. The book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing offers complete understanding of the basic scientific principles needed to perform image processing, gap filling, data merging, data fusion, machine learning, and feature extraction. Written by two experts in remote sensing, the book presents the required basic concepts, tools, algorithms, platforms, and technology hubs toward advanced integration. By merging and fusing data sets collected from different satellite sensors with common features, we are enabled to utilize the strength of each satellite sensor to the maximum extent. The inclusion of machine learning or data mining techniques to aid in feature extraction after gap filling, data merging and/or data fusion further empowers earth observation, leading to confirm the whole is greater than the sum of its parts. Contemporary applications discussed in this book make all essential knowledge seamlessly integrated by an interdisciplinary manner. These case-based engineering practices uniquely illustrate how to improve such an emerging field of importance to cope with the most challenging real-world environmental monitoring issues.


Author : Florence Tupin
Jordi Inglada
Publisher : John Wiley & Sons
Release : 2014-02-19
Page : 368
Category : Technology & Engineering
ISBN 13 : 1118898923
Description :


Dedicated to remote sensing images, from their acquisition to theiruse in various applications, this book covers the global lifecycleof images, including sensors and acquisition systems, applicationssuch as movement monitoring or data assimilation, and image anddata processing. It is organized in three main parts. The first part presentstechnological information about remote sensing (choice of satelliteorbit and sensors) and elements of physics related to sensing(optics and microwave propagation). The second part presents imageprocessing algorithms and their specificities for radar or optical,multi and hyper-spectral images. The final part is devoted toapplications: change detection and analysis of time series,elevation measurement, displacement measurement and dataassimilation. Offering a comprehensive survey of the domain of remote sensingimagery with a multi-disciplinary approach, this book is suitablefor graduate students and engineers, with backgrounds either incomputer science and applied math (signal and image processing) orgeo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Herresearch interests include remote sensing imagery, image analysisand interpretation, three-dimensional reconstruction, and syntheticaperture radar, especially for urban remote sensingapplications. Jordi Inglada works at the Centre National d’ÉtudesSpatiales (French Space Agency), Toulouse, France, in the field ofremote sensing image processing at the CESBIO laboratory. He is incharge of the development of image processing algorithms for theoperational exploitation of Earth observation images, mainly in thefield of multi-temporal image analysis for land use and coverchange. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signaland Imaging department. His research interests include the modelingand processing of synthetic aperture radar images.


Author : C.H. Chen
Publisher : CRC Press
Release : 2007-10-17
Page : 400
Category : Technology & Engineering
ISBN 13 : 9781420066654
Description :


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


Author : Robert A. Schowengerdt
Publisher : Elsevier
Release : 2012-12-02
Page : 522
Category : Technology & Engineering
ISBN 13 : 0080516106
Description :


This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms. Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, spatial, and geometric models are used to introduce advanced image processing techniques such as hyperspectral image analysis, fusion of multisensor images, and digital elevationmodel extraction from stereo imagery. The material is suited for graduate level engineering, physical and natural science courses, or practicing remote sensing scientists. Each chapter is enhanced by student exercises designed to stimulate an understanding of the material. Over 300 figuresare produced specifically for this book, and numerous tables provide a rich bibliography of the research literature.


Author : Soad Ibrahim
Publisher :
Release : 2012
Page :
Category :
ISBN 13 :
Description :



Author : H.B. Mitchell
Publisher : Springer Science & Business Media
Release : 2010-03-16
Page : 247
Category : Technology & Engineering
ISBN 13 : 9783642112164
Description :


The purpose of this book is to provide a practical introduction to the th- ries, techniques and applications of image fusion. The present work has been designed as a textbook for a one-semester ?nal-year undergraduate, or ?r- year graduate, course in image fusion. It should also be useful to practising engineers who wish to learn the concepts of image fusion and apply them to practical applications. In addition, the book may also be used as a supp- mentary text for a graduate course on topics in advanced image processing. The book complements the author’s previous work on multi-sensor data [1] fusion by concentrating exclusively on the theories, techniques and app- cations of image fusion. The book is intended to be self-contained in so far as the subject of image fusion is concerned, although some prior exposure to the ?eld of computer vision and image processing may be helpful to the reader. Apart from two preliminary chapters, the book is divided into three parts.


Author : Anil Kumar
Priyadarshi Upadhyay
Publisher : CRC Press
Release : 2020-08-30
Page : 194
Category : Computers
ISBN 13 : 1000091546
Description :


This book covers the state-of-art image classification methods for discrimination of earth objects from remote sensing satellite data with an emphasis on fuzzy machine learning and deep learning algorithms. Both types of algorithms are described in such details that these can be implemented directly for thematic mapping of multiple-class or specific-class landcover from multispectral optical remote sensing data. These algorithms along with multi-date, multi-sensor remote sensing are capable to monitor specific stage (for e.g., phenology of growing crop) of a particular class also included. With these capabilities fuzzy machine learning algorithms have strong applications in areas like crop insurance, forest fire mapping, stubble burning, post disaster damage mapping etc. It also provides details about the temporal indices database using proposed Class Based Sensor Independent (CBSI) approach supported by practical examples. As well, this book addresses other related algorithms based on distance, kernel based as well as spatial information through Markov Random Field (MRF)/Local convolution methods to handle mixed pixels, non-linearity and noisy pixels. Further, this book covers about techniques for quantiative assessment of soft classified fraction outputs from soft classification and supported by in-house developed tool called sub-pixel multi-spectral image classifier (SMIC). It is aimed at graduate, postgraduate, research scholars and working professionals of different branches such as Geoinformation sciences, Geography, Electrical, Electronics and Computer Sciences etc., working in the fields of earth observation and satellite image processing. Learning algorithms discussed in this book may also be useful in other related fields, for example, in medical imaging. Overall, this book aims to: exclusive focus on using large range of fuzzy classification algorithms for remote sensing images; discuss ANN, CNN, RNN, and hybrid learning classifiers application on remote sensing images; describe sub-pixel multi-spectral image classifier tool (SMIC) to support discussed fuzzy and learning algorithms; explain how to assess soft classified outputs as fraction images using fuzzy error matrix (FERM) and its advance versions with FERM tool, Entropy, Correlation Coefficient, Root Mean Square Error and Receiver Operating Characteristic (ROC) methods and; combines explanation of the algorithms with case studies and practical applications.