Hyperspectral Image Analysis
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Hyperspectral Image Analysis
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Author : Saurabh Prasad
language : en
Publisher: Springer
Release Date : 2020-06-09
Hyperspectral Image Analysis written by Saurabh Prasad and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-09 with Computers categories.
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.
Techniques And Applications Of Hyperspectral Image Analysis
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Author : Hans Grahn
language : en
Publisher: John Wiley & Sons
Release Date : 2007-09-27
Techniques And Applications Of Hyperspectral Image Analysis written by Hans Grahn 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 2007-09-27 with Science categories.
Techniques and Applications of Hyperspectral Image Analysis gives an introduction to the field of image analysis using hyperspectral techniques, and includes definitions and instrument descriptions. Other imaging topics that are covered are segmentation, regression and classification. The book discusses how high quality images of large data files can be structured and archived. Imaging techniques also demand accurate calibration, and are covered in sections about multivariate calibration techniques. The book explains the most important instruments for hyperspectral imaging in more technical detail. A number of applications from medical and chemical imaging are presented and there is an emphasis on data analysis including modeling, data visualization, model testing and statistical interpretation.
Deep Learning For Hyperspectral Image Analysis And Classification
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Author : Linmi Tao
language : en
Publisher: Springer Nature
Release Date : 2021-02-20
Deep Learning For Hyperspectral Image Analysis And Classification written by Linmi Tao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-20 with Computers categories.
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.
Hyperspectral Imaging Analysis And Applications For Food Quality
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Author : N.C. Basantia
language : en
Publisher: CRC Press
Release Date : 2018-11-16
Hyperspectral Imaging Analysis And Applications For Food Quality written by N.C. Basantia and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-16 with Technology & Engineering categories.
In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes. Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives.
Advanced Image Processing Techniques For Remotely Sensed Hyperspectral Data
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Author : Pramod K. Varshney
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-08-12
Advanced Image Processing Techniques For Remotely Sensed Hyperspectral Data written by Pramod K. Varshney and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-08-12 with Computers categories.
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.
Hyperspectral Imaging For Food Quality Analysis And Control
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Author : Da-Wen Sun
language : en
Publisher: Academic Press
Release Date : 2010
Hyperspectral Imaging For Food Quality Analysis And Control written by Da-Wen Sun and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Science categories.
Based on the integration of computer vision and spectrscopy techniques, hyperspectral imaging is a novel technology for obtaining both spatial and spectral information on a product. Used for nearly 20 years in the aerospace and military industries, more recently hyperspectral imaging has emerged and matured into one of the most powerful and rapidly growing methods of non-destructive food quality analysis and control. Hyperspectral Imaging for Food Quality Analysis and Control provides the core information about how this proven science can be practically applied for food quality assessment, including information on the equipment available and selection of the most appropriate of those instruments. Additionally, real-world food-industry-based examples are included, giving the reader important insights into the actual application of the science in evaluating food products. *Presentation of principles and instruments provides core understanding of how this science performs, as well as guideline on selecting the most appropriate equipment for implementation *Includes real-world, practical application to demonstrate the viability and challenges of working with this technology *Provides necessary information for making correct determination on use of hyperspectral imaging
Hyperspectral Imaging Remote Sensing
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Author : Dimitris G. Manolakis
language : en
Publisher: Cambridge University Press
Release Date : 2016-10-20
Hyperspectral Imaging Remote Sensing written by Dimitris G. Manolakis 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 2016-10-20 with Computers categories.
Understand the seminal principles, current techniques, and tools of imaging spectroscopy with this self-contained introductory guide.
Hyperspectral Data Processing
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Author : Chein-I Chang
language : en
Publisher: John Wiley & Sons
Release Date : 2013-02-01
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 2013-02-01 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.
Hyperspectral Imaging
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Author : Chein-I Chang
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-11
Hyperspectral Imaging written by Chein-I Chang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Computers categories.
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.
Processing And Analysis Of Hyperspectral Data
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Author : Jie Chen
language : en
Publisher:
Release Date : 2020
Processing And Analysis Of Hyperspectral Data written by Jie Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Hyperspectral imaging categories.