Hyperspectral Image Fusion

Hyperspectral Image Fusion

Author: Subhasis Chaudhuri

Publisher: Springer Science & Business Media

Published: 2013-05-25

Total Pages: 200

ISBN-13: 1461474701

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Hyperspectral Image Fusion is the first text dedicated to the fusion techniques for such a huge volume of data consisting of a very large number of images. This monograph brings out recent advances in the research in the area of visualization of hyperspectral data. It provides a set of pixel-based fusion techniques, each of which is based on a different framework and has its own advantages and disadvantages. The techniques are presented with complete details so that practitioners can easily implement them. It is also demonstrated how one can select only a few specific bands to speed up the process of fusion by exploiting spatial correlation within successive bands of the hyperspectral data. While the techniques for fusion of hyperspectral images are being developed, it is also important to establish a framework for objective assessment of such techniques. This monograph has a dedicated chapter describing various fusion performance measures that are applicable to hyperspectral image fusion. This monograph also presents a notion of consistency of a fusion technique which can be used to verify the suitability and applicability of a technique for fusion of a very large number of images. This book will be a highly useful resource to the students, researchers, academicians and practitioners in the specific area of hyperspectral image fusion, as well as generic image fusion.


Book Synopsis Hyperspectral Image Fusion by : Subhasis Chaudhuri

Download or read book Hyperspectral Image Fusion written by Subhasis Chaudhuri and published by Springer Science & Business Media. This book was released on 2013-05-25 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral Image Fusion is the first text dedicated to the fusion techniques for such a huge volume of data consisting of a very large number of images. This monograph brings out recent advances in the research in the area of visualization of hyperspectral data. It provides a set of pixel-based fusion techniques, each of which is based on a different framework and has its own advantages and disadvantages. The techniques are presented with complete details so that practitioners can easily implement them. It is also demonstrated how one can select only a few specific bands to speed up the process of fusion by exploiting spatial correlation within successive bands of the hyperspectral data. While the techniques for fusion of hyperspectral images are being developed, it is also important to establish a framework for objective assessment of such techniques. This monograph has a dedicated chapter describing various fusion performance measures that are applicable to hyperspectral image fusion. This monograph also presents a notion of consistency of a fusion technique which can be used to verify the suitability and applicability of a technique for fusion of a very large number of images. This book will be a highly useful resource to the students, researchers, academicians and practitioners in the specific area of hyperspectral image fusion, as well as generic image fusion.

Hyperspectral Image Analysis

Hyperspectral Image Analysis

Author: Saurabh Prasad

Publisher: Springer Nature

Published: 2020-04-27

Total Pages: 464

ISBN-13: 3030386171

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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.


Book Synopsis Hyperspectral Image Analysis by : Saurabh Prasad

Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Image Processing Techniques for Remotely Sensed Hyperspectral Data

Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

Author: Pramod K. Varshney

Publisher: Springer Science & Business Media

Published: 2004-08-12

Total Pages: 344

ISBN-13: 9783540216681

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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.


Book Synopsis Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data by : Pramod K. Varshney

Download or read book Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data written by Pramod K. Varshney and published by Springer Science & Business Media. This book was released on 2004-08-12 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Remote Sensing Image Fusion

Remote Sensing Image Fusion

Author: Luciano Alparone

Publisher: CRC Press

Published: 2015-03-06

Total Pages: 328

ISBN-13: 1466587504

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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


Book Synopsis Remote Sensing Image Fusion by : Luciano Alparone

Download or read book Remote Sensing Image Fusion written by Luciano Alparone and published by CRC Press. This book was released on 2015-03-06 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Hyperspectral Imaging

Hyperspectral Imaging

Author:

Publisher: Elsevier

Published: 2019-09-29

Total Pages: 800

ISBN-13: 0444639780

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Hyperspectral Imaging, Volume 32, presents a comprehensive exploration of the different analytical methodologies applied on hyperspectral imaging and a state-of-the-art analysis of applications in different scientific and industrial areas. This book presents, for the first time, a comprehensive collection of the main multivariate algorithms used for hyperspectral image analysis in different fields of application. The benefits, drawbacks and suitability of each are fully discussed, along with examples of their application. Users will find state-of-the art information on the machinery for hyperspectral image acquisition, along with a critical assessment of the usage of hyperspectral imaging in diverse scientific fields. Provides a comprehensive roadmap of hyperspectral image analysis, with benefits and considerations for each method discussed Covers state-of-the-art applications in different scientific fields Discusses the implementation of hyperspectral devices in different environments


Book Synopsis Hyperspectral Imaging by :

Download or read book Hyperspectral Imaging written by and published by Elsevier. This book was released on 2019-09-29 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral Imaging, Volume 32, presents a comprehensive exploration of the different analytical methodologies applied on hyperspectral imaging and a state-of-the-art analysis of applications in different scientific and industrial areas. This book presents, for the first time, a comprehensive collection of the main multivariate algorithms used for hyperspectral image analysis in different fields of application. The benefits, drawbacks and suitability of each are fully discussed, along with examples of their application. Users will find state-of-the art information on the machinery for hyperspectral image acquisition, along with a critical assessment of the usage of hyperspectral imaging in diverse scientific fields. Provides a comprehensive roadmap of hyperspectral image analysis, with benefits and considerations for each method discussed Covers state-of-the-art applications in different scientific fields Discusses the implementation of hyperspectral devices in different environments

The Future of Hyperspectral Imaging

The Future of Hyperspectral Imaging

Author: Stefano Selci

Publisher: MDPI

Published: 2019-11-20

Total Pages: 220

ISBN-13: 3039218220

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This book includes some very recent applications and the newest emerging trends of hyper-spectral imaging (HSI). HSI is a very recent and strange beast, a sort of a melting pot of previous techniques and scientific interests, merging and concentrating the efforts of physicists, chemists, botanists, biologists, and physicians, to mention just a few, as well as experts in data crunching and statistical elaboration. For almost a century, scientific observation, from looking to planets and stars down to our own cells and below, could be divided into two main categories: analyzing objects on the basis of their physical dimension (recording size, position, weight, etc. and their variations) or on how the object emits, reflects, or absorbs part of the electromagnetic spectrum, i.e., spectroscopy. While the two aspects have been obviously entangled, instruments and skills have always been clearly distinct from each other. With HSI now available, this is no longer the case. This instrument can return specimen dimensionalities and spectroscopic properties to any single pixel of your specimen, in a single set of data. HSI modality is ubiquitous and scale-invariant enough to be used to mark terrestrial resources on the basis of a land map obtained from satellite observation (actually, the oldest application of this type) or to understand if the cell you are looking at is cancerous or perfectly healthy. For all these reasons, HSI represents one of the most exciting methodologies of the new millennium.


Book Synopsis The Future of Hyperspectral Imaging by : Stefano Selci

Download or read book The Future of Hyperspectral Imaging written by Stefano Selci and published by MDPI. This book was released on 2019-11-20 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes some very recent applications and the newest emerging trends of hyper-spectral imaging (HSI). HSI is a very recent and strange beast, a sort of a melting pot of previous techniques and scientific interests, merging and concentrating the efforts of physicists, chemists, botanists, biologists, and physicians, to mention just a few, as well as experts in data crunching and statistical elaboration. For almost a century, scientific observation, from looking to planets and stars down to our own cells and below, could be divided into two main categories: analyzing objects on the basis of their physical dimension (recording size, position, weight, etc. and their variations) or on how the object emits, reflects, or absorbs part of the electromagnetic spectrum, i.e., spectroscopy. While the two aspects have been obviously entangled, instruments and skills have always been clearly distinct from each other. With HSI now available, this is no longer the case. This instrument can return specimen dimensionalities and spectroscopic properties to any single pixel of your specimen, in a single set of data. HSI modality is ubiquitous and scale-invariant enough to be used to mark terrestrial resources on the basis of a land map obtained from satellite observation (actually, the oldest application of this type) or to understand if the cell you are looking at is cancerous or perfectly healthy. For all these reasons, HSI represents one of the most exciting methodologies of the new millennium.

2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS).

2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS).

Author:

Publisher:

Published: 2019

Total Pages:

ISBN-13: 9781728152943

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Book Synopsis 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). by :

Download or read book 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Advances in Hyperspectral Image Processing Techniques

Advances in Hyperspectral Image Processing Techniques

Author: Chein-I Chang

Publisher: John Wiley & Sons

Published: 2022-11-09

Total Pages: 612

ISBN-13: 1119687772

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Advances in Hyperspectral Image Processing Techniques Authoritative and comprehensive resource covering recent hyperspectral imaging techniques from theory to applications Advances in Hyperspectral Image Processing Techniques is derived from recent developments of hyperspectral imaging (HSI) techniques along with new applications in the field, covering many new ideas that have been explored and have led to various new directions in the past few years. The work gathers an array of disparate research into one resource and explores its numerous applications across a wide variety of disciplinary areas. In particular, it includes an introductory chapter on fundamentals of HSI and a chapter on extensive use of HSI techniques in satellite on-orbit and on-board processing to aid readers involved in these specific fields. The book’s content is based on the expertise of invited scholars and is categorized into six parts. Part I provides general theory. Part II presents various Band Selection techniques for Hyperspectral Images. Part III reviews recent developments on Compressive Sensing for Hyperspectral Imaging. Part IV includes Fusion of Hyperspectral Images. Part V covers Hyperspectral Data Unmixing. Part VI offers different views on Hyperspectral Image Classification. Specific sample topics covered in Advances in Hyperspectral Image Processing Techniques include: Two fundamental principles of hyperspectral imaging Constrained band selection for hyperspectral imaging and class information-based band selection for hyperspectral image classification Restricted entropy and spectrum properties for hyperspectral imaging and endmember finding in compressively sensed band domain Hyperspectral and LIDAR data fusion, fusion of band selection methods for hyperspectral imaging, and fusion using multi-dimensional information Advances in spectral unmixing of hyperspectral data and fully constrained least squares linear spectral mixture analysis Sparse representation-based hyperspectral image classification; collaborative hyperspectral image classification; class-feature weighted hyperspectral image classification; target detection approach to hyperspectral image classification With many applications beyond traditional remote sensing, ranging from defense and intelligence, to agriculture, to forestry, to environmental monitoring, to food safety and inspection, to medical imaging, Advances in Hyperspectral Image Processing Techniques is an essential resource on the topic for industry professionals, researchers, academics, and graduate students working in the field.


Book Synopsis Advances in Hyperspectral Image Processing Techniques by : Chein-I Chang

Download or read book Advances in Hyperspectral Image Processing Techniques written by Chein-I Chang and published by John Wiley & Sons. This book was released on 2022-11-09 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Hyperspectral Image Processing Techniques Authoritative and comprehensive resource covering recent hyperspectral imaging techniques from theory to applications Advances in Hyperspectral Image Processing Techniques is derived from recent developments of hyperspectral imaging (HSI) techniques along with new applications in the field, covering many new ideas that have been explored and have led to various new directions in the past few years. The work gathers an array of disparate research into one resource and explores its numerous applications across a wide variety of disciplinary areas. In particular, it includes an introductory chapter on fundamentals of HSI and a chapter on extensive use of HSI techniques in satellite on-orbit and on-board processing to aid readers involved in these specific fields. The book’s content is based on the expertise of invited scholars and is categorized into six parts. Part I provides general theory. Part II presents various Band Selection techniques for Hyperspectral Images. Part III reviews recent developments on Compressive Sensing for Hyperspectral Imaging. Part IV includes Fusion of Hyperspectral Images. Part V covers Hyperspectral Data Unmixing. Part VI offers different views on Hyperspectral Image Classification. Specific sample topics covered in Advances in Hyperspectral Image Processing Techniques include: Two fundamental principles of hyperspectral imaging Constrained band selection for hyperspectral imaging and class information-based band selection for hyperspectral image classification Restricted entropy and spectrum properties for hyperspectral imaging and endmember finding in compressively sensed band domain Hyperspectral and LIDAR data fusion, fusion of band selection methods for hyperspectral imaging, and fusion using multi-dimensional information Advances in spectral unmixing of hyperspectral data and fully constrained least squares linear spectral mixture analysis Sparse representation-based hyperspectral image classification; collaborative hyperspectral image classification; class-feature weighted hyperspectral image classification; target detection approach to hyperspectral image classification With many applications beyond traditional remote sensing, ranging from defense and intelligence, to agriculture, to forestry, to environmental monitoring, to food safety and inspection, to medical imaging, Advances in Hyperspectral Image Processing Techniques is an essential resource on the topic for industry professionals, researchers, academics, and graduate students working in the field.

Graph Spectral Image Processing

Graph Spectral Image Processing

Author: Gene Cheung

Publisher: John Wiley & Sons

Published: 2021-08-31

Total Pages: 322

ISBN-13: 1789450284

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Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing – extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels – provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements. The book is divided into two parts. The first is centered on the fundamentals of graph signal processing theories, including graph filtering, graph learning and graph neural networks. The second part details several imaging applications using graph signal processing tools, including image and video compression, 3D image compression, image restoration, point cloud processing, image segmentation and image classification, as well as the use of graph neural networks for image processing.


Book Synopsis Graph Spectral Image Processing by : Gene Cheung

Download or read book Graph Spectral Image Processing written by Gene Cheung and published by John Wiley & Sons. This book was released on 2021-08-31 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph spectral image processing is the study of imaging data from a graph frequency perspective. Modern image sensors capture a wide range of visual data including high spatial resolution/high bit-depth 2D images and videos, hyperspectral images, light field images and 3D point clouds. The field of graph signal processing – extending traditional Fourier analysis tools such as transforms and wavelets to handle data on irregular graph kernels – provides new flexible computational tools to analyze and process these varied types of imaging data. Recent methods combine graph signal processing ideas with deep neural network architectures for enhanced performances, with robustness and smaller memory requirements. The book is divided into two parts. The first is centered on the fundamentals of graph signal processing theories, including graph filtering, graph learning and graph neural networks. The second part details several imaging applications using graph signal processing tools, including image and video compression, 3D image compression, image restoration, point cloud processing, image segmentation and image classification, as well as the use of graph neural networks for image processing.

Remote Sensing Imagery

Remote Sensing Imagery

Author: Florence Tupin

Publisher: John Wiley & Sons

Published: 2014-02-19

Total Pages: 277

ISBN-13: 1118898923

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Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle of images, including sensors and acquisition systems, applications such as movement monitoring or data assimilation, and image and data processing. It is organized in three main parts. The first part presents technological information about remote sensing (choice of satellite orbit and sensors) and elements of physics related to sensing (optics and microwave propagation). The second part presents image processing algorithms and their specificities for radar or optical, multi and hyper-spectral images. The final part is devoted to applications: change detection and analysis of time series, elevation measurement, displacement measurement and data assimilation. Offering a comprehensive survey of the domain of remote sensing imagery with a multi-disciplinary approach, this book is suitable for graduate students and engineers, with backgrounds either in computer science and applied math (signal and image processing) or geo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Her research interests include remote sensing imagery, image analysis and interpretation, three-dimensional reconstruction, and synthetic aperture radar, especially for urban remote sensing applications. Jordi Inglada works at the Centre National d’Études Spatiales (French Space Agency), Toulouse, France, in the field of remote sensing image processing at the CESBIO laboratory. He is in charge of the development of image processing algorithms for the operational exploitation of Earth observation images, mainly in the field of multi-temporal image analysis for land use and cover change. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signal and Imaging department. His research interests include the modeling and processing of synthetic aperture radar images.


Book Synopsis Remote Sensing Imagery by : Florence Tupin

Download or read book Remote Sensing Imagery written by Florence Tupin and published by John Wiley & Sons. This book was released on 2014-02-19 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle of images, including sensors and acquisition systems, applications such as movement monitoring or data assimilation, and image and data processing. It is organized in three main parts. The first part presents technological information about remote sensing (choice of satellite orbit and sensors) and elements of physics related to sensing (optics and microwave propagation). The second part presents image processing algorithms and their specificities for radar or optical, multi and hyper-spectral images. The final part is devoted to applications: change detection and analysis of time series, elevation measurement, displacement measurement and data assimilation. Offering a comprehensive survey of the domain of remote sensing imagery with a multi-disciplinary approach, this book is suitable for graduate students and engineers, with backgrounds either in computer science and applied math (signal and image processing) or geo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Her research interests include remote sensing imagery, image analysis and interpretation, three-dimensional reconstruction, and synthetic aperture radar, especially for urban remote sensing applications. Jordi Inglada works at the Centre National d’Études Spatiales (French Space Agency), Toulouse, France, in the field of remote sensing image processing at the CESBIO laboratory. He is in charge of the development of image processing algorithms for the operational exploitation of Earth observation images, mainly in the field of multi-temporal image analysis for land use and cover change. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signal and Imaging department. His research interests include the modeling and processing of synthetic aperture radar images.