Non Linear Spectral Unmixing Of Hyperspectral Data
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Non Linear Spectral Unmixing Of Hyperspectral Data
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Author : Somdatta Chakravortty
language : en
Publisher: CRC Press
Release Date : 2024-08-21
Non Linear Spectral Unmixing Of Hyperspectral Data written by Somdatta Chakravortty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-21 with Technology & Engineering categories.
This book is based on satellite image processing, focusing on the potential of hyperspectral image processing (HIP) research with a case study-based approach. It covers the background, objectives, and practical issues related to HIP and substantiates the needs and potentials of said technology for discrimination of pure and mixed endmembers in pixels, including unsupervised target detection algorithms for extraction of unknown spectra of pure pixels. It includes application of machine learning and deep learning models on hyperspectral data and its role in spatial big data analytics. Features include the following: Focuses on capability of hyperspectral data in characterization of linear and non-linear interactions of a natural forest biome. Illustrates modeling the ecodynamics of mangrove habitats in the coastal ecosystem. Discusses adoption of appropriate technique for handling spatial data (with coarse resolution). Covers machine learning and deep learning models for classification. Implements non-linear spectral unmixing for identifying fractional abundance of diverse mangrove species of coastal Sundarbans. This book is aimed at researchers and graduate students in digital image processing, big data, and spatial informatics.
Non Linear Spectral Unmixing Of Hyperspectral Data
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Author : Somdatta Chakravortty
language : en
Publisher:
Release Date : 2025
Non Linear Spectral Unmixing Of Hyperspectral Data written by Somdatta Chakravortty and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Artificial satellites in remote sensing categories.
"This book is based on satellite image processing focussing on the potential of hyperspectral image processing (HIP) research taking a case study-based approach. It covers the background, objectives, and practical issues related to HIP and substantiates the needs/potentials of said technology for discrimination of pure and mixed endmembers in pixels including unsupervised target detection algorithms for extraction of unknown spectra of pure pixels. It includes application of machine and deep learning models on hyperspectral data and its role in spatial big data analytics. Features: Focusses on capability of hyperspectral data in characterization of linear and non-linear interactions of a natural forest biome; Illustrates modelling the eco-dynamics of mangrove habitats in the coastal ecosystem; Discusses adoption of appropriate technique for handling spatial data (with coarse resolution); Covers machine/deep learning models for classification; Implements non-linear spectral unmixing for identifying fractional abundance of diverse mangrove species of Coastal Sunderbans; This book is aimed at researchers and graduate students in digital image processing, big data, and spatial informatics"--
Hyperspectral Imaging In Agriculture Food And Environment
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Author : Alejandro Isabel Luna Maldonado
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-08-01
Hyperspectral Imaging In Agriculture Food And Environment written by Alejandro Isabel Luna Maldonado and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-01 with Technology & Engineering categories.
This book is about the novel aspects and future trends of the hyperspectral imaging in agriculture, food, and environment. The topics covered by this book are hyperspectral imaging and their applications in the nondestructive quality assessment of fruits and vegetables, hyperspectral imaging for assessing quality and safety of meat, multimode hyperspectral imaging for food quality and safety, models fitting to pattern recognition in hyperspectral images, sequential classification of hyperspectral images, graph construction for hyperspectral data unmixing, target visualization method to process hyperspectral image, and soil contamination mapping with hyperspectral imagery. This book is a general reference work for students, professional engineers, and readers with interest in the subject.
Resolving Spectral Mixtures
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Author :
language : en
Publisher: Elsevier
Release Date : 2016-08-13
Resolving Spectral Mixtures written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-13 with Computers categories.
Resolving Spectral Mixtures: With Applications from Ultrafast Time-Resolved Spectroscopy to Superresolution Imaging offers a comprehensive look into the most important models and frameworks essential to resolving the spectral unmixing problem—from multivariate curve resolution and multi-way analysis to Bayesian positive source separation and nonlinear unmixing. Unravelling total spectral data into the contributions from individual unknown components with limited prior information is a complex problem that has attracted continuous interest for almost four decades. Spectral unmixing is a topic of interest in statistics, chemometrics, signal processing, and image analysis. For decades, researchers from these fields were often unaware of the work in other disciplines due to their different scientific and technical backgrounds and interest in different objects or samples. This led to the development of quite different approaches to solving the same problem. This multi-authored book will bridge the gap between disciplines with contributions from a number of well-known and strongly active chemometric and signal processing research groups. Among chemists, multivariate curve resolution methods are preferred to extract information about the nature, amount, and location in time (process) and space (imaging and microscopy) of chemical constituents in complex samples. In signal processing, assumptions are usually around statistical independence of the extracted components. However, the chapters include the complexity of the spectral data to be unmixed as well as dimensionality and size of the data sets. Advanced spectroscopy is the key thread linking the different chapters. Applications cover a large part of the electromagnetic spectrum. Time-resolution ranges from femtosecond to second in process spectroscopy and spatial resolution covers the submicronic to macroscopic scale in hyperspectral imaging. - Demonstrates how and why data analysis, signal processing, and chemometrics are essential to the spectral unmixing problem - Guides the reader through the fundamentals and details of the different methods - Presents extensive plots, graphical representations, and illustrations to help readers understand the features of different techniques and to interpret results - Bridges the gap between disciplines with contributions from a number of well-known and highly active chemometric and signal processing research groups
Theory Of Reflectance And Emittance Spectroscopy
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Author : Bruce Hapke
language : en
Publisher: Cambridge University Press
Release Date : 2012-01-19
Theory Of Reflectance And Emittance Spectroscopy written by Bruce Hapke and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-19 with Technology & Engineering categories.
Reflectance and emittance spectroscopy are increasingly important tools in remote sensing and have been employed in most recent planetary spacecraft missions. They are primarily used to measure properties of disordered materials, especially in the interpretation of remote observations of the surfaces of the Earth and other terrestrial planets. This book gives a quantitative treatment of the physics of the interaction of electromagnetic radiation with particulate media, such as powders and soils. Subjects covered include electromagnetic wave propagation, single particle scattering, diffuse reflectance, thermal emittance and polarisation. This new edition has been updated to include a quantitative treatment of the effects of porosity, a detailed discussion of the coherent backscatter opposition effect, a quantitative treatment of simultaneous transport of energy within the medium by conduction and radiation, and lists of relevant databases and software. This is an essential reference for research scientists, engineers and advanced students of planetary remote sensing.
Hyperspectral Remote Sensing
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Author : Ruiliang Pu
language : en
Publisher: CRC Press
Release Date : 2017-08-16
Hyperspectral Remote Sensing written by Ruiliang Pu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-16 with Science categories.
Advanced imaging spectral technology and hyperspectral analysis techniques for multiple applications are the key features of the book. This book will present in one volume complete solutions from concepts, fundamentals, and methods of acquisition of hyperspectral data to analyses and applications of the data in a very coherent manner. It will help readers to fully understand basic theories of HRS, how to utilize various field spectrometers and bioinstruments, the importance of radiometric correction and atmospheric correction, the use of analysis, tools and software, and determine what to do with HRS technology and data.
Hyperspectral Remote Sensing Of Vegetation Second Edition Four Volume Set
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Author : Prasad S. Thenkabail
language : en
Publisher: CRC Press
Release Date : 2022-07-30
Hyperspectral Remote Sensing Of Vegetation Second Edition Four Volume Set written by Prasad S. Thenkabail and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-30 with Technology & Engineering categories.
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics Volume II, Hyperspectral Indices and Image Classifications for Agriculture and Vegetation evaluates the performance of hyperspectral narrowband or imaging spectroscopy data with specific emphasis on the uses and applications of hyperspectral narrowband vegetation indices in characterizing, modeling, mapping, and monitoring agricultural crops and vegetation Volume III, Biophysical and Biochemical Characterization and Plant Species Studies demonstrates the methods that are developed and used to study terrestrial vegetation using hyperspectral data. This volume includes extensive discussions on hyperspectral data processing and how to implement data processing mechanisms for specific biophysical and biochemical applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessments Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection.
Hyperspectral Data Processing
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Author : Chein-I Chang
language : en
Publisher: John Wiley & Sons
Release Date : 2013-04-08
Hyperspectral Data Processing written by Chein-I Chang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-08 with Technology & Engineering categories.
Hyperspectral Data Processing: Algorithm Design and Analysis is a culmination of the research conducted in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Specifically, it treats hyperspectral image processing and hyperspectral signal processing as separate subjects in two different categories. Most materials covered in this book can be used in conjunction with the author’s first book, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, without much overlap. Many results in this book are either new or have not been explored, presented, or published in the public domain. These include various aspects of endmember extraction, unsupervised linear spectral mixture analysis, hyperspectral information compression, hyperspectral signal coding and characterization, as well as applications to conceal target detection, multispectral imaging, and magnetic resonance imaging. Hyperspectral Data Processing contains eight major sections: Part I: provides fundamentals of hyperspectral data processing Part II: offers various algorithm designs for endmember extraction Part III: derives theory for supervised linear spectral mixture analysis Part IV: designs unsupervised methods for hyperspectral image analysis Part V: explores new concepts on hyperspectral information compression Parts VI & VII: develops techniques for hyperspectral signal coding and characterization Part VIII: presents applications in multispectral imaging and magnetic resonance imaging Hyperspectral Data Processing compiles an algorithm compendium with MATLAB codes in an appendix to help readers implement many important algorithms developed in this book and write their own program codes without relying on software packages. Hyperspectral Data Processing is a valuable reference for those who have been involved with hyperspectral imaging and its techniques, as well those who are new to the subject.
Proceedings Of The Global Ai Congress 2019
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Author : Jyotsna Kumar Mandal
language : en
Publisher: Springer Nature
Release Date : 2020-04-02
Proceedings Of The Global Ai Congress 2019 written by Jyotsna Kumar Mandal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-02 with Technology & Engineering categories.
This book gathers high-quality research papers presented at the Global AI Congress 2019, which was organized by the Institute of Engineering and Management, Kolkata, India, on 12–14 September 2019. Sharing contributions prepared by researchers, practitioners, developers and experts in the areas of artificial intelligence, the book covers the areas of AI for E-commerce and web applications, AI and sensors, augmented reality, big data, brain computing interfaces, computer vision, cognitive radio networks, data mining, deep learning, expert systems, fuzzy sets and systems, image processing, knowledge representation, nature-inspired computing, quantum machine learning, reasoning, robotics and autonomous systems, robotics and the IoT, social network analysis, speech processing, video processing, and virtual reality.
Fundamentals Sensor Systems Spectral Libraries And Data Mining For Vegetation
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Author : Prasad S. Thenkabail
language : en
Publisher: CRC Press
Release Date : 2018-12-07
Fundamentals Sensor Systems Spectral Libraries And Data Mining For Vegetation written by Prasad S. Thenkabail and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Technology & Engineering categories.
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics. This book also presents and discusses hyperspectral narrowband data acquired in numerous unique spectral bands in the entire length of the spectrum from various ground-based, airborne, and spaceborne platforms. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume I through the editors’ perspective. Key Features of Volume I: Provides the fundamentals of hyperspectral remote sensing used in agricultural crops and vegetation studies. Discusses the latest advances in hyperspectral remote sensing of ecosystems and croplands. Develops online hyperspectral libraries, proximal sensing and phenotyping for understanding, modeling, mapping, and monitoring crop and vegetation traits. Implements reflectance spectroscopy of soils and vegetation. Enumerates hyperspectral data mining and data processing methods, approaches, and machine learning algorithms. Explores methods and approaches for data mining and overcoming data redundancy; Highlights the advanced methods for hyperspectral data processing steps by developing or implementing appropriate algorithms and coding the same for processing on a cloud computing platform like the Google Earth Engine. Integrates hyperspectral with other data, such as the LiDAR data, in the study of vegetation. Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.