Download or read book Non Linear Spectral Unmixing of Hyperspectral Data written by Somdatta Chakravortty and published by CRC Press. This book was released on 2024-08-21 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Non linear Unmixing for Hyperspectral Reflectance of Pigment Mixtures Using Derivative Transformation and Convolutional Neural Networks written by Sohyun An and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cultural heritage science encompasses the conservation, analysis, and interpretation of artworks, objects, and materials that hold archaeological, historic, and artistic value. It involves a wide range of disciplines and methodologies aimed at preserving and understanding our collective cultural heritage. Hyperspectral imaging (HSI) is recognized as a highly effective tool in the field of Cultural Heritage Science. Its primary advantage stems from its capability to acquire reflectance data from across a wide range of spectral bands for each pixel, providing high-dimensional vectors that enable advanced visual data analysis. Its superior spectral resolution makes it particularly effective for polychrome artifact characterization, facilitating non-invasive investigations of original painting materials, including pigments and binders. Moreover, HSI enables the identification of alteration products and underdrawings providing valuable insights into the composition and physical history of cultural artifacts. However, owing to the intricate hierarchical structure of painted artifacts, nonlinear spectral unmixing methods are often used to process HSI data. These methods facilitate the breakdown of pigment mixtures and enable the detection of individual components. In recent years, there has been a growing emphasis on data-driven approaches to effectively manage and analyze the vast volumes of hyperspectral imaging data involved in advanced spectral unmixing techniques. In line with this trend, this research endeavors to harness the power of convolutional neural networks (CNNs) for the nonlinear unmixing of hyperspectral reflectance spectra in pigment mixtures. By leveraging the capabilities of CNNs, this study aims to enhance the efficiency and accuracy of spectral unmixing, paving the way for a more robust and comprehensive analysis of complex pigment mixtures in cultural heritage objects. In contrast to traditional approaches that heavily rely on predefined assumptions, by harnessing the power of machine learning and leveraging the inherent patterns within the data, this approach enables the extraction of meaningful and significant results without being constrained by predetermined assumptions. In this research, the neural network's training set was limited to a small number of samples with various fractions of indigo and yellow ochre. Exploiting the extensive spectral information provided by each pixel in hyperspectral imaging (HSI), a substantial dataset for training was generated. Through rigorous experimentation involving different combinations of input features, it was determined that the optimal input configuration consists of the reflectance data derived from the HSI, complemented by the inclusion of the first derivative transformation value. The developed multi-input convolutional neural network model demonstrates high accuracy in estimating the proportion of indigo and yellow ochre in the mixture, as evidenced by the mean absolute error, mean squared error, and variance score of 0.01, 0.03, and 0.9999, respectively. Moreover, the model's predicted average values closely align with the correct fractions, further affirming its precision. Notably, even for fractions that were not included in the training set, the model demonstrates a high level of accuracy, albeit slightly lower than the results for the trained set. In conclusion, this research establishes the efficacy of the multi-input CNN model in accurately estimating the fraction of indigo and yellow ochre in pigment mixtures. The model successfully leverages hyperspectral imaging (HSI) data to index each pixel and provide precise mapping of the pigments. Moreover, the model's versatility enables its application to different pigment mixtures with minimal additional effort, encompassing the fabrication of mixtures, HSI data acquisition, and CNN training.

Download or read book Theory of Reflectance and Emittance Spectroscopy written by Bruce Hapke and published by Cambridge University Press. This book was released on 2012-01-19 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential reference for researchers and students of planetary remote sensing on the interaction of electromagnetic radiation with planetary surfaces.

Download or read book Hyperspectral Imaging in Agriculture Food and Environment written by Alejandro Isabel Luna Maldonado and published by BoD – Books on Demand. This book was released on 2018-08-01 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

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

Download or read book Hyperspectral Data Processing written by Chein-I Chang and published by John Wiley & Sons. This book was released on 2013-02-01 with total page 1180 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Hyperspectral Data Processing written by Chein-I Chang and published by John Wiley & Sons. This book was released on 2013-04-08 with total page 1180 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Hyperspectral Remote Sensing written by Ruiliang Pu and published by CRC Press. This book was released on 2017-08-16 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Handbook of Blind Source Separation written by Pierre Comon and published by Academic Press. This book was released on 2010-02-17 with total page 856 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book reflects recent results in signal processing and numerical analysis, and includes topics such as optimization criteria, mathematical tools, the design of numerical algorithms, convolutive mixtures, and time frequency approaches. This Handbook is an ideal reference for university researchers, R&D engineers and graduates wishing to learn the core principles, methods, algorithms, and applications of Blind Source Separation. Covers the principles and major techniques and methods in one book Edited by the pioneers in the field with contributions from 34 of the world’s experts Describes the main existing numerical algorithms and gives practical advice on their design Covers the latest cutting edge topics: second order methods; algebraic identification of under-determined mixtures, time-frequency methods, Bayesian approaches, blind identification under non negativity approaches, semi-blind methods for communications Shows the applications of the methods to key application areas such as telecommunications, biomedical engineering, speech, acoustic, audio and music processing, while also giving a general method for developing applications

Download or read book Knowledge Guided Machine Learning written by Anuj Karpatne and published by CRC Press. This book was released on 2022-08-15 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. Yet, these "black-box" ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing "data-only" or "scientific knowledge-only" methods to use knowledge and data at an equal footing. Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness to the problem formulations and research methods in this emerging field. Knowledge Guided Machine Learning: Accelerating Discovery using Scientific Knowledge and Data provides an introduction to this rapidly growing field by discussing some of the common themes of research in KGML using illustrative examples, case studies, and reviews from diverse application domains and research communities as book chapters by leading researchers. KEY FEATURES First-of-its-kind book in an emerging area of research that is gaining widespread attention in the scientific and data science fields Accessible to a broad audience in data science and scientific and engineering fields Provides a coherent organizational structure to the problem formulations and research methods in the emerging field of KGML using illustrative examples from diverse application domains Contains chapters by leading researchers, which illustrate the cutting-edge research trends, opportunities, and challenges in KGML research from multiple perspectives Enables cross-pollination of KGML problem formulations and research methods across disciplines Highlights critical gaps that require further investigation by the broader community of researchers and practitioners to realize the full potential of KGML

Download or read book Optical Remote Sensing written by Saurabh Prasad and published by Springer Science & Business Media. This book was released on 2011-03-23 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data. Challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, pattern classification and target recognition, visualization of high dimensional imagery.

Download or read book Hyperspectral Data Exploitation written by Chein-I Chang and published by John Wiley & Sons. This book was released on 2007-06-11 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Authored by a panel of experts in the field, this book focuses on hyperspectral image analysis, systems, and applications. With discussion of application-based projects and case studies, this professional reference will bring you up-to-date on this pervasive technology, wether you are working in the military and defense fields, or in remote sensing technology, geoscience, or agriculture.

Download or read book Internet of Things Applications and Future written by Atef Zaki Ghalwash and published by Springer Nature. This book was released on 2020-04-03 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of the best research papers presented at the First World Conference on Internet of Things: Applications & Future (ITAF 2019), Sponsored by GR Foundation and French University in Egypt, held at Triumph Luxury Hotel, Cairo, Egypt, on 14–15 October 2019. It includes innovative works from leading researchers, innovators, business executives, and industry professionals that cover the latest advances in and applications for commercial and industrial end users across sectors within the emerging Internet of Things ecosphere. It addresses both current and emerging topics related to the Internet of Things such as big data research, new services and analytics, Internet of Things (IoT) fundamentals, electronic computation and analysis, big data for multi-discipline services, security, privacy and trust, IoT technologies, and open and cloud technologies.

Download or read book Blind Speech Separation written by Shoji Makino and published by Springer Science & Business Media. This book was released on 2007-09-07 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the world’s first edited book on independent component analysis (ICA)-based blind source separation (BSS) of convolutive mixtures of speech. This book brings together a small number of leading researchers to provide tutorial-like and in-depth treatment on major ICA-based BSS topics, with the objective of becoming the definitive source for current, comprehensive, authoritative, and yet accessible treatment.

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:

Download or read book Proceedings of ELM 2014 Volume 2 written by Jiuwen Cao and published by Springer. This book was released on 2014-12-09 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains some selected papers from the International Conference on Extreme Learning Machine 2014, which was held in Singapore, December 8-10, 2014. This conference brought together the researchers and practitioners of Extreme Learning Machine (ELM) from a variety of fields to promote research and development of “learning without iterative tuning”. The book covers theories, algorithms and applications of ELM. It gives the readers a glance of the most recent advances of ELM.