Machine Vision And Advanced Image Processing In Remote Sensing

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Machine Vision and Advanced Image Processing in Remote Sensing

Ioannis Kanellopoulos,Graeme G. Wilkinson,Theo Moons
Machine Vision and Advanced Image Processing in Remote Sensing Book PDF

Author : Ioannis Kanellopoulos,Graeme G. Wilkinson,Theo Moons
Publisher : Springer Science & Business Media
Page : 339 pages
File Size : 53,8 Mb
Release : 2012-12-06
Category : Science
ISBN : 9783642601057

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Machine Vision and Advanced Image Processing in Remote Sensing by Ioannis Kanellopoulos,Graeme G. Wilkinson,Theo Moons Pdf

Since 1994, the European Commission has undertaken various actions to expand the use of Earth observation (EO) from space in the Union and to stimulate value-added services based on the use of Earth observation satellite data.' By supporting research and technological development activities in this area, DG XII responded to the need to increase the cost-effectiveness of space derived environmental information. At the same time, it has contributed to a better exploitation of this unique technology, which is a key source of data for environmental monitoring from local to global scale. MAVIRIC is part of the investment made in the context of the Environ ment and Climate Programme (1994-1998) to strengthen applied techniques, based on a better understanding of the link between the remote sensing signal and the underlying bio- geo-physical processes. Translation of this scientific know-how into practical algorithms or methods is a priority in order to con vert more quickly, effectively and accurately space signals into geographical information. Now the availability of high spatial resolution satellite data is rapidly evolving and the fusion of data from different sensors including radar sensors is progressing well, the question arises whether existing machine vision approaches could be advantageously used by the remote sensing community. Automatic feature/object extraction from remotely sensed images looks very attractive in terms of processing time, standardisation and implementation of operational processing chains, but it remains highly complex when applied to natural scenes.

Remote Sensing Image Processing

Gustavo Camps-Valls,Devis Tuia,Luis Gómez-Chova,Sandra Jiménez,Jesus Malo
Remote Sensing Image Processing Book PDF

Author : Gustavo Camps-Valls,Devis Tuia,Luis Gómez-Chova,Sandra Jiménez,Jesus Malo
Publisher : Springer Nature
Page : 242 pages
File Size : 50,7 Mb
Release : 2022-06-01
Category : Technology & Engineering
ISBN : 9783031022470

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Remote Sensing Image Processing by Gustavo Camps-Valls,Devis Tuia,Luis Gómez-Chova,Sandra Jiménez,Jesus Malo Pdf

Earth observation is the field of science concerned with the problem of monitoring and modeling the processes on the Earth surface and their interaction with the atmosphere. The Earth is continuously monitored with advanced optical and radar sensors. The images are analyzed and processed to deliver useful products to individual users, agencies and public administrations. To deal with these problems, remote sensing image processing is nowadays a mature research area, and the techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, data coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This book covers some of the fields in a comprehensive way. Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / Classification / Spectral Mixture Analysis / Estimation of Physical Parameters

Remote Sensing Image Processing

Gustavo Camps-Valls
Remote Sensing Image Processing Book PDF

Author : Gustavo Camps-Valls
Publisher : Morgan & Claypool Publishers
Page : 195 pages
File Size : 41,5 Mb
Release : 2011
Category : Computers
ISBN : 9781608458196

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Remote Sensing Image Processing by Gustavo Camps-Valls Pdf

Earth observation is the field of science concerned with the problem of monitoring and modeling the processes on the Earth surface and their interaction with the atmosphere. The Earth is continuously monitored with advanced optical and radar sensors. The images are analyzed and processed to deliver useful products to individual users, agencies and public administrations. To deal with these problems, remote sensing image processing is nowadays a mature research area, and the techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, data coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This book covers some of the fields in a comprehensive way. Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / {Classification / Spectral Mixture Analysis / Estimation of Physical Parameters

Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images

Yakoub Bazi,Edoardo Pasolli
Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images Book PDF

Author : Yakoub Bazi,Edoardo Pasolli
Publisher : MDPI
Page : 438 pages
File Size : 55,9 Mb
Release : 2021-06-15
Category : Science
ISBN : 9783036509860

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Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images by Yakoub Bazi,Edoardo Pasolli Pdf

The rapid growth of the world population has resulted in an exponential expansion of both urban and agricultural areas. Identifying and managing such earthly changes in an automatic way poses a worth-addressing challenge, in which remote sensing technology can have a fundamental role to answer—at least partially—such demands. The recent advent of cutting-edge processing facilities has fostered the adoption of deep learning architectures owing to their generalization capabilities. In this respect, it seems evident that the pace of deep learning in the remote sensing domain remains somewhat lagging behind that of its computer vision counterpart. This is due to the scarce availability of ground truth information in comparison with other computer vision domains. In this book, we aim at advancing the state of the art in linking deep learning methodologies with remote sensing image processing by collecting 20 contributions from different worldwide scientists and laboratories. The book presents a wide range of methodological advancements in the deep learning field that come with different applications in the remote sensing landscape such as wildfire and postdisaster damage detection, urban forest mapping, vine disease and pavement marking detection, desert road mapping, road and building outline extraction, vehicle and vessel detection, water identification, and text-to-image matching.

Signal and Image Processing for Remote Sensing

C.H. Chen
Signal and Image Processing for Remote Sensing Book PDF

Author : C.H. Chen
Publisher : CRC Press
Page : 433 pages
File Size : 54,7 Mb
Release : 2024-06-11
Category : Technology & Engineering
ISBN : 9781040031254

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Signal and Image Processing for Remote Sensing by C.H. Chen Pdf

Advances in signal and image processing for remote sensing have been tremendous in recent years. The progress has been particularly significant with the use of deep learning based techniques to solve remote sensing problems. These advancements are the focus of this third edition of Signal and Image Processing for Remote Sensing. It emphasizes the use of machine learning approaches for the extraction of remote sensing information. Other topics include change detection in remote sensing and compressed sensing. With 19 new chapters written by world leaders in the field, this book provides an authoritative examination and offers a unique point of view on signal and image processing. Features Includes all new content and does not replace the previous edition Covers machine learning approaches in both signal and image processing for remote sensing Studies deep learning methods for remote sensing information extraction that is found in other books Explains SAR, microwave, seismic, GPR, and hyperspectral sensors and all sensors considered Discusses improved pattern classification approaches and compressed sensing approaches Provides ample examples of each aspect of both signal and image processing This book is intended for university academics, researchers, postgraduate students, industry, and government professionals who use remote sensing and its applications.

Advanced Digital Image Processing and Its Applications in Big Data

Ankur Dumka,Alaknanda Ashok,Parag Verma,Poonam Verma
Advanced Digital Image Processing and Its Applications in Big Data Book PDF

Author : Ankur Dumka,Alaknanda Ashok,Parag Verma,Poonam Verma
Publisher : CRC Press
Page : 237 pages
File Size : 50,5 Mb
Release : 2020-12-09
Category : Computers
ISBN : 9781000281316

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Advanced Digital Image Processing and Its Applications in Big Data by Ankur Dumka,Alaknanda Ashok,Parag Verma,Poonam Verma Pdf

This book covers the technology of digital image processing in various fields with big data and their applications. Readers will understand various technologies and strategies used in digital image processing as well as handling big data, using machine-learning techniques. This book will help to improve the skills of students and researchers in such fields as engineering, agriculture, and medical imaging. There is a need to be able to understand and analyse the latest developments of digital image technology. As such, this book will cover: · Applications such as biomedical science and biometric image processing, content-based image retrieval, remote sensing, pattern recognition, shape and texture analysis · New concepts in color interpolation to produce the full color from the sub-pattern bare pattern color prevalent in today's digital cameras and other imaging devices · Image compression standards that are needed to serve diverse applications · Applications of remote sensing, medical science, traffic management, education, innovation, and analysis in agricultural design and image processing · Both soft and hard computing approaches at great length in relation to major image processing tasks · The direction and development of current and future research in many areas of image processing · A comprehensive bibliography for additional research (integrated within the framework of the book) This book focuses not only on theoretical and practical knowledge in the field but also on the traditional and latest tools and techniques adopted in image processing and data science. It also provides an indispensable guide to a wide range of basic and advanced techniques in the fields of image processing and data science.

Hyperspectral Image Analysis

Saurabh Prasad,Jocelyn Chanussot
Hyperspectral Image Analysis Book PDF

Author : Saurabh Prasad,Jocelyn Chanussot
Publisher : Springer Nature
Page : 464 pages
File Size : 53,7 Mb
Release : 2020-04-27
Category : Computers
ISBN : 9783030386177

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Hyperspectral Image Analysis by Saurabh Prasad,Jocelyn Chanussot Pdf

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

Advanced Sensing in Image Processing and IoT

Rashmi Gupta,Arun Kumar Rana,Sachin Dhawan,Korhan Cengiz
Advanced Sensing in Image Processing and IoT Book PDF

Author : Rashmi Gupta,Arun Kumar Rana,Sachin Dhawan,Korhan Cengiz
Publisher : CRC Press
Page : 380 pages
File Size : 51,7 Mb
Release : 2021-03-26
Category : Computers
ISBN : 9781000543025

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Advanced Sensing in Image Processing and IoT by Rashmi Gupta,Arun Kumar Rana,Sachin Dhawan,Korhan Cengiz Pdf

The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations. Key sailing Features: The impact of the proposed book is to provide a major area of concern to develop a foundation for the implementation process of new image processing and IoT devices based on Energy, Industry, and Healthcare related technology. The researchers working on image processing and IoT devices can correlate their work with other requirements of advanced technology in Energy, Industry, and Healthcare domain. To make aware of the latest technology like AI and Machine learning in Energy, Industry, and Healthcare related technology. Useful for the researcher to explore new things like Security, cryptography, and privacy in Energy, Industry, and Healthcare related technology. People who want to start in Energy, Industry, and Healthcare related technology with image processing and IoT world.

Math Physics Foundation of Advanced Remote Sensing Digital Image Processing

Lei Yan,Hongying Zhao,Yi Lin,Yanbiao Sun
Math Physics Foundation of Advanced Remote Sensing Digital Image Processing Book PDF

Author : Lei Yan,Hongying Zhao,Yi Lin,Yanbiao Sun
Publisher : Springer
Page : 0 pages
File Size : 40,6 Mb
Release : 2023-06-24
Category : Technology & Engineering
ISBN : 9819917778

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Math Physics Foundation of Advanced Remote Sensing Digital Image Processing by Lei Yan,Hongying Zhao,Yi Lin,Yanbiao Sun Pdf

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.

Remote Sensing

Robert A. Schowengerdt
Remote Sensing Book PDF

Author : Robert A. Schowengerdt
Publisher : Unknown
Page : 522 pages
File Size : 42,5 Mb
Release : 1997
Category : Image processing
ISBN : OCLC:840072723

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Remote Sensing by Robert A. Schowengerdt Pdf

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.

Computer Vision in Advanced Control Systems-5

Margarita N. Favorskaya,Lakhmi C. Jain
Computer Vision in Advanced Control Systems 5 Book PDF

Author : Margarita N. Favorskaya,Lakhmi C. Jain
Publisher : Springer Nature
Page : 329 pages
File Size : 49,7 Mb
Release : 2019-12-07
Category : Technology & Engineering
ISBN : 9783030337957

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Computer Vision in Advanced Control Systems-5 by Margarita N. Favorskaya,Lakhmi C. Jain Pdf

This book applies novel theories to improve algorithms in complex data analysis in various fields, including object detection, remote sensing, data transmission, data fusion, gesture recognition, and medical image processing and analysis. It is intended for Ph.D. students, academics, researchers, and software developers working in the areas of digital video processing and computer vision technologies.

Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification

Anil Kumar,Priyadarshi Upadhyay,A. Senthil Kumar
Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification Book PDF

Author : Anil Kumar,Priyadarshi Upadhyay,A. Senthil Kumar
Publisher : CRC Press
Page : 194 pages
File Size : 52,6 Mb
Release : 2020-07-19
Category : Computers
ISBN : 9781000091526

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Fuzzy Machine Learning Algorithms for Remote Sensing Image Classification by Anil Kumar,Priyadarshi Upadhyay,A. Senthil Kumar Pdf

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.

Augmented Vision Perception in Infrared

Riad I. Hammoud
Augmented Vision Perception in Infrared Book PDF

Author : Riad I. Hammoud
Publisher : Springer Science & Business Media
Page : 476 pages
File Size : 55,6 Mb
Release : 2009-01-01
Category : Science
ISBN : 9781848002777

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Augmented Vision Perception in Infrared by Riad I. Hammoud Pdf

Throughout much of machine vision’s early years the infrared imagery has suffered from return on investment despite its advantages over visual counterparts. Recently, the ?scal momentum has switched in favor of both manufacturers and practitioners of infrared technology as a result of today’s rising security and safety challenges and advances in thermographic sensors and their continuous drop in costs. This yielded a great impetus in achieving ever better performance in remote surveillance, object recognition, guidance, noncontact medical measurements, and more. The purpose of this book is to draw attention to recent successful efforts made on merging computer vision applications (nonmilitary only) and nonvisual imagery, as well as to ?ll in the need in the literature for an up-to-date convenient reference on machine vision and infrared technologies. Augmented Perception in Infrared provides a comprehensive review of recent deployment of infrared sensors in modern applications of computer vision, along with in-depth description of the world’s best machine vision algorithms and intel- gent analytics. Its topics encompass many disciplines of machine vision, including remote sensing, automatic target detection and recognition, background modeling and image segmentation, object tracking, face and facial expression recognition, - variant shape characterization, disparate sensors fusion, noncontact physiological measurements, night vision, and target classi?cation. Its application scope includes homeland security, public transportation, surveillance, medical, and military. Mo- over, this book emphasizes the merging of the aforementioned machine perception applications and nonvisual imaging in intensi?ed, near infrared, thermal infrared, laser, polarimetric, and hyperspectral bands.

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

Pramod K. Varshney,Manoj K. Arora
Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data Book PDF

Author : Pramod K. Varshney,Manoj K. Arora
Publisher : Springer Science & Business Media
Page : 323 pages
File Size : 48,8 Mb
Release : 2013-03-09
Category : Science
ISBN : 9783662056059

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Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data by Pramod K. Varshney,Manoj K. Arora Pdf

The first of its kind, this book reviews image processing tools and techniques including Independent Component Analysis, Mutual Information, Markov Random Field Models and Support Vector Machines. The book also explores a number of experimental examples based on a variety of remote sensors. The book will be useful to people involved in hyperspectral imaging research, as well as by remote-sensing data like geologists, hydrologists, environmental scientists, civil engineers and computer scientists.

Learning to Understand Remote Sensing Images

Qi Wang
Learning to Understand Remote Sensing Images Book PDF

Author : Qi Wang
Publisher : MDPI
Page : 376 pages
File Size : 48,9 Mb
Release : 2019-09-30
Category : Computers
ISBN : 9783038976981

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Learning to Understand Remote Sensing Images by Qi Wang Pdf

With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.