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Spectral Spatial Classification Of Hyperspectral Remote Sensing Images
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Book Synopsis Spectral-Spatial Classification of Hyperspectral Remote Sensing Images by : Jon Atli Benediktsson
Download or read book Spectral-Spatial Classification of Hyperspectral Remote Sensing Images written by Jon Atli Benediktsson and published by Artech House. This book was released on 2015-09-01 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive new resource brings you up to date on recent developments in the classification of hyperspectral images using both spectral and spatial information, including advanced statistical approaches and methods. The inclusion of spatial information to traditional approaches for hyperspectral classification has been one of the most active and relevant innovative lines of research in remote sensing during recent years. This book gives you insight into several important challenges when performing hyperspectral image classification related to the imbalance between high dimensionality and limited availability of training samples, or the presence of mixed pixels in the data. This book also shows you how to integrate spatial and spectral information in order to take advantage of the benefits that both sources of information provide.
Book Synopsis Spectral-spatial Classification of Hyperspectral Remote Sensing Images by : Jón Atli Benediktsson
Download or read book Spectral-spatial Classification of Hyperspectral Remote Sensing Images written by Jón Atli Benediktsson and published by Artech House Publishers. This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive new resource brings you up to date on recent developments in the classification of hyperspectral images using both spectral and spatial information, including advanced statistical approaches and methods. The inclusion of spatial information to traditional approaches for hyperspectral classification has been one of the most active and relevant innovative lines of research in remote sensing during recent years. This book gives you insight into several important challenges when performing hyperspectral image classification related to the imbalance between high dimensionality and limited availability of training samples, or the presence of mixed pixels in the data. This book also shows you how to integrate spatial and spectral information in order to take advantage of the benefits that both sources of information provide.
Book Synopsis Classification of Hyperspectral Remote Sensing Images by :
Download or read book Classification of Hyperspectral Remote Sensing Images written by and published by . This book was released on 2018-05 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in hyperspectral remote sensor technology allow the simultaneous acquisition of hundreds of spectral wavelengths for each image pixel. Hyperspectral imaging systems can acquire numerous contiguous spectral bands throughout the electromagnetic spectrum. Therefore, hyperspectral imaging techniques are widely used for many applications, including environmental monitoring, mineralogy, astronomy, surveillance and defense. Nevertheless, the high dimensionality of the pixels, undesirable noise, high spectral redundancy and spectral and spatial variabilities, in conjunction with limited ground truth data, present challenges for the analysis of hyperspectral imagery. The classification technology is currently the predominate method for analyzing hyperspectral images and has received much attention. Over the past decades, numerous pixel-wise classification methods, which only use spectral information, have been proposed to classify remote sensing images. Recent advances in spectral-spatial classification of hyperspectral images are presented in this book. Several techniques are investigated for combining both spatial and spectral information. The book highlights the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validates the proposed methods. Spectral-Spatial Classification of Hyperspectral Remote Sensing Images presents insight into numerous important challenges when performing hyperspectral image classification related to the imbalance between high dimensionality and limited availability of training samples, or the presence of mixed pixels in the data. The book also demonstrates the reader how to integrate spatial and spectral information in order to take advantage of the benefits that both sources of information provide.
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.
Book Synopsis Hyperspectral Remote Sensing by : Prem Chandra Pandey
Download or read book Hyperspectral Remote Sensing written by Prem Chandra Pandey and published by Elsevier. This book was released on 2020-08-05 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral Remote Sensing: Theory and Applications offers the latest information on the techniques, advances and wide-ranging applications of hyperspectral remote sensing, such as forestry, agriculture, water resources, soil and geology, among others. The book also presents hyperspectral data integration with other sources, such as LiDAR, Multi-spectral data, and other remote sensing techniques. Researchers who use this resource will be able to understand and implement the technology and data in their respective fields. As such, it is a valuable reference for researchers and data analysts in remote sensing and Earth Observation fields and those in ecology, agriculture, hydrology and geology. Includes the theory of hyperspectral remote sensing, along with techniques and applications across a variety of disciplines Presents the processing, methods and techniques utilized for hyperspectral remote sensing and in-situ data collection Provides an overview of the state-of-the-art, including algorithms, techniques and case studies
Book Synopsis Deep Learning for Hyperspectral Image Analysis and Classification by : Linmi Tao
Download or read book Deep Learning for Hyperspectral Image Analysis and Classification written by Linmi Tao and published by Springer Nature. This book was released on 2021-02-20 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on deep learning-based methods for hyperspectral image (HSI) analysis. Unsupervised spectral-spatial adaptive band-noise factor-based formulation is devised for HSI noise detection and band categorization. The method to characterize the bands along with the noise estimation of HSIs will benefit subsequent remote sensing techniques significantly. This book develops on two fronts: On the one hand, it is aimed at domain professionals who want to have an updated overview of how hyperspectral acquisition techniques can combine with deep learning architectures to solve specific tasks in different application fields. On the other hand, the authors want to target the machine learning and computer vision experts by giving them a picture of how deep learning technologies are applied to hyperspectral data from a multidisciplinary perspective. The presence of these two viewpoints and the inclusion of application fields of remote sensing by deep learning are the original contributions of this review, which also highlights some potentialities and critical issues related to the observed development trends.
Book Synopsis Hyperspectral Image Processing by : Liguo Wang
Download or read book Hyperspectral Image Processing written by Liguo Wang and published by Springer. This book was released on 2015-07-15 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.
Book Synopsis Hyperspectral Remote Sensing and Spectral Signature Applications by : S. Rajendran
Download or read book Hyperspectral Remote Sensing and Spectral Signature Applications written by S. Rajendran and published by New India Publishing. This book was released on 2009 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contributed papers presented at the National Seminar on "Hyperspectral Remote Sensing and Spectral Signature Databse Management System," held on February 14-15, 2008 at Annamalai University.
Book Synopsis Hyperspectral Remote Sensing by : Ruiliang Pu
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 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
Book Synopsis Processing and Analysis of Hyperspectral Data by : Jie Chen
Download or read book Processing and Analysis of Hyperspectral Data written by Jie Chen and published by BoD – Books on Demand. This book was released on 2020-01-22 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applications, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods.
Book Synopsis Hyperspectral Imaging by : Chein-I Chang
Download or read book Hyperspectral Imaging written by Chein-I Chang and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral Imaging: Techniques for Spectral Detection and Classification is an outgrowth of the research conducted over the years in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. It explores applications of statistical signal processing to hyperspectral imaging and further develops non-literal (spectral) techniques for subpixel detection and mixed pixel classification. This text is the first of its kind on the topic and can be considered a recipe book offering various techniques for hyperspectral data exploitation. In particular, some known techniques, such as OSP (Orthogonal Subspace Projection) and CEM (Constrained Energy Minimization) that were previously developed in the RSSIPL, are discussed in great detail. This book is self-contained and can serve as a valuable and useful reference for researchers in academia and practitioners in government and industry.
Book Synopsis Hyperspectral Remote Sensing of Vegetation by : Prasad S. Thenkabail
Download or read book Hyperspectral Remote Sensing of Vegetation written by Prasad S. Thenkabail and published by CRC Press. This book was released on 2016-04-19 with total page 782 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modeling forest canopy biochemical properties, detecting crop stress and disease, mapping leaf chlorophyll content as it influences crop production, identifying plants affected by contaminants such as arsenic, demonstrating sensitivity to plant nitrogen content, classifying vegetation species and type, characterizing wetlands, and mapping invasive species. The need for significant improvements in quantifying, modeling, and mapping plant chemical, physical, and water properties is more critical than ever before to reduce uncertainties in our understanding of the Earth and to better sustain it. There is also a need for a synthesis of the vast knowledge spread throughout the literature from more than 40 years of research. Hyperspectral Remote Sensing of Vegetation integrates this knowledge, guiding readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Taking a practical approach to a complex subject, the book demonstrates the experience, utility, methods and models used in studying vegetation using hyperspectral data. Written by leading experts, including pioneers in the field, each chapter presents specific applications, reviews existing state-of-the-art knowledge, highlights the advances made, and provides guidance for the appropriate use of hyperspectral data in the study of vegetation as well as its numerous applications, such as crop yield modeling, crop and vegetation biophysical and biochemical property characterization, and crop moisture assessment. This comprehensive book brings together the best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, vegetation classification, biophysical and biochemical modeling, crop productivity and water productivity mapping, and modeling. It provides the pertinent facts, synthesizing findings so that readers can get the correct picture on issues such as the best wavebands for their practical applications, methods of analysis using whole spectra, hyperspectral vegetation indices targeted to study specific biophysical and biochemical quantities, and methods for detecting parameters such as crop moisture variability, chlorophyll content, and stress levels. A collective "knowledge bank," it guides professionals to adopt the best practices for their own work.
Book Synopsis Remote Sensing Image Processing by : Gustavo Camps-Valls
Download or read book Remote Sensing Image Processing written by Gustavo Camps-Valls and published by Morgan & Claypool Publishers. This book was released on 2011-12-11 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus) by : IEEE Staff
Download or read book 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus) written by IEEE Staff and published by . This book was released on 2021-01-26 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference will cover a broad area of electrical and electronic engineering, computer science and engineering, biomedical engineering, industrial management It is targeted on results of research carried out by young researchers (Master and PhD students, engineers)
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 2013-03-09 with total page 323 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.
Author :Michael Theodore Eismann Publisher :SPIE-International Society for Optical Engineering ISBN 13 :9780819487872 Total Pages :0 pages Book Rating :4.4/5 (878 download)
Book Synopsis Hyperspectral Remote Sensing by : Michael Theodore Eismann
Download or read book Hyperspectral Remote Sensing written by Michael Theodore Eismann and published by SPIE-International Society for Optical Engineering. This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hyperspectral remote sensing is an emerging, multidisciplinary field with diverse applications that builds on the principles of material spectroscopy, radiative transfer, imaging spectrometry, and hyperspectral data processing. While there are many resources that suitably cover these areas individually and focus on specific aspects of the hyperspectral remote sensing field, this book provides a holistic treatment that captures its multidisciplinary nature. The content is oriented toward the physical principles of hyperspectral remote sensing as opposed to applications of hyperspectral technology. Readers can expect to finish the book armed with the required knowledge to understand the immense literature available in this technology area and apply their knowledge to the understanding of material spectral properties, the design of hyperspectral systems, the analysis of hyperspectral imagery, and the application of the technology to specific problems.
