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Author: Chein-I Chang Publisher: John Wiley & Sons ISBN: 1118269772 Category : Technology & Engineering Languages : en Pages : 1164
Book Description
Hyperspectral Data Processing: Algorithm Design andAnalysis is a culmination of the research conducted in theRemote Sensing Signal and Image Processing Laboratory (RSSIPL) atthe University of Maryland, Baltimore County. Specifically, ittreats hyperspectral image processing and hyperspectral signalprocessing as separate subjects in two different categories. Mostmaterials covered in this book can be used in conjunction with theauthor’s first book, Hyperspectral Imaging: Techniques forSpectral Detection and Classification, without muchoverlap. Many results in this book are either new or have not beenexplored, presented, or published in the public domain. Theseinclude various aspects of endmember extraction, unsupervisedlinear spectral mixture analysis, hyperspectral informationcompression, hyperspectral signal coding and characterization, aswell as applications to conceal target detection, multispectralimaging, and magnetic resonance imaging. Hyperspectral DataProcessing contains eight major sections: Part I: provides fundamentals of hyperspectral dataprocessing Part II: offers various algorithm designs for endmemberextraction Part III: derives theory for supervised linear spectral mixtureanalysis Part IV: designs unsupervised methods for hyperspectral imageanalysis Part V: explores new concepts on hyperspectral informationcompression Parts VI & VII: develops techniques for hyperspectralsignal coding and characterization Part VIII: presents applications in multispectral imaging andmagnetic resonance imaging Hyperspectral Data Processing compiles an algorithmcompendium with MATLAB codes in an appendix to help readersimplement many important algorithms developed in this book andwrite their own program codes without relying on softwarepackages. Hyperspectral Data Processing is a valuable reference forthose who have been involved with hyperspectral imaging and itstechniques, as well those who are new to the subject.
Author: Chein-I Chang Publisher: John Wiley & Sons ISBN: 1118269772 Category : Technology & Engineering Languages : en Pages : 1164
Book Description
Hyperspectral Data Processing: Algorithm Design andAnalysis is a culmination of the research conducted in theRemote Sensing Signal and Image Processing Laboratory (RSSIPL) atthe University of Maryland, Baltimore County. Specifically, ittreats hyperspectral image processing and hyperspectral signalprocessing as separate subjects in two different categories. Mostmaterials covered in this book can be used in conjunction with theauthor’s first book, Hyperspectral Imaging: Techniques forSpectral Detection and Classification, without muchoverlap. Many results in this book are either new or have not beenexplored, presented, or published in the public domain. Theseinclude various aspects of endmember extraction, unsupervisedlinear spectral mixture analysis, hyperspectral informationcompression, hyperspectral signal coding and characterization, aswell as applications to conceal target detection, multispectralimaging, and magnetic resonance imaging. Hyperspectral DataProcessing contains eight major sections: Part I: provides fundamentals of hyperspectral dataprocessing Part II: offers various algorithm designs for endmemberextraction Part III: derives theory for supervised linear spectral mixtureanalysis Part IV: designs unsupervised methods for hyperspectral imageanalysis Part V: explores new concepts on hyperspectral informationcompression Parts VI & VII: develops techniques for hyperspectralsignal coding and characterization Part VIII: presents applications in multispectral imaging andmagnetic resonance imaging Hyperspectral Data Processing compiles an algorithmcompendium with MATLAB codes in an appendix to help readersimplement many important algorithms developed in this book andwrite their own program codes without relying on softwarepackages. Hyperspectral Data Processing is a valuable reference forthose who have been involved with hyperspectral imaging and itstechniques, as well those who are new to the subject.
Author: Chein-I Chang Publisher: John Wiley & Sons ISBN: 0471690562 Category : Technology & Engineering Languages : en Pages : 1180
Book Description
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.
Author: Jie Chen Publisher: BoD – Books on Demand ISBN: 1789851092 Category : Science Languages : en Pages : 137
Book Description
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.
Author: Pramod K. Varshney Publisher: Springer Science & Business Media ISBN: 3662056054 Category : Science Languages : en Pages : 323
Book Description
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: Chein-I Chang Publisher: Springer Science & Business Media ISBN: 9780306474835 Category : Computers Languages : en Pages : 400
Book Description
Explores the application 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 anc can be considered a recipe book offering various techniques for hyperspectral data exploitation.
Author: Chein-I Chang Publisher: John Wiley & Sons ISBN: 047012461X Category : Science Languages : en Pages : 442
Book Description
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.
Author: Viktor V. Krasnoproshin Publisher: Springer ISBN: 3319542206 Category : Computers Languages : en Pages : 181
Book Description
This book constitutes the refereed proceedings of the 13th International Conference on Pattern Recognition and Information Processing, PRIP 2016, held in Minsk, Belarus, in October 2016. The 18 revised full papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on summarizing lectures; pattern recognition and image analysis; information processing and applications.
Author: Danail Stoyanov Publisher: Springer ISBN: 3319075217 Category : Medical Languages : en Pages : 278
Book Description
This book constitutes the refereed proceedings of the 5th International Conference on Information Processing in Computer-Assisted Interventions, IPCAI 2014, held in Fukuoka, Japan, on June 28, 2014. The 28 papers presented were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on planning, simulation, patient specific models for computer assisted interventions, medical robotics and surgical navigation, interventional imaging and advanced intra-op visualization, cognition, modeling and context awareness, clinical applications, systems, software, and validation.
Author: Chein-I Chang
Author: Chein-I Chang
Author: Jie Chen
Author: Chein-I Chang
Author: Jie Chen
Author: Pramod K. Varshney
Author: Chein-I Chang
Author: Chein-I Chang
Author: Lin Yun
Author: Viktor V. Krasnoproshin
Author: Danail Stoyanov