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:
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
CHEIN-I CHANG, PhD, is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County. He established the Remote Sensing Signal and Image Processing Laboratory and conducts research in designing and developing signal processing algorithms for hyperspectral imaging, medical imaging, and documentation analysis. A Fellow of IEEE and SPIE, Dr. Chang has published over 125 refereed journal articles, including more than forty papers in the IEEE Transaction on Geoscience and Remote Sensing. In addition to authoring Hyperspectral Imaging: Techniques for Spectral Detection and Classification, as well as editing two books, Hyperspectral Data Exploitation: Theory and Applications and Recent Advances in Hyperspectral Signal and Imaging Processing and co-editing one book, High Performance Computing in Remote Sensing, he holds five patents and has several pending.
A comprehensive reference on advanced hyperspectral imaging
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:
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Descrizione libro Gebunden. Condizione: New. CHEIN-I CHANG, PhD, is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County. He established the Remote Sensing Signal and Image Processing Laboratory and conducts research in designing . Codice articolo 556562035
Descrizione libro Condizione: New. Codice articolo 2425333-n
Descrizione libro Hardcover. Condizione: new. Hardcover. 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 authors 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 processingPart II: offers various algorithm designs for endmember extractionPart III: derives theory for supervised linear spectral mixture analysisPart IV: designs unsupervised methods for hyperspectral image analysisPart V: explores new concepts on hyperspectral information compressionParts VI & VII: develops techniques for hyperspectral signal coding and characterizationPart 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 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780471690566
Descrizione libro Condizione: New. Codice articolo 2425333-n
Descrizione libro Hardcover. Condizione: new. Hardcover. 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 authors 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 processingPart II: offers various algorithm designs for endmember extractionPart III: derives theory for supervised linear spectral mixture analysisPart IV: designs unsupervised methods for hyperspectral image analysisPart V: explores new concepts on hyperspectral information compressionParts VI & VII: develops techniques for hyperspectral signal coding and characterizationPart 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 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9780471690566
Descrizione libro Hardcover. Condizione: new. Hardcover. 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 authors 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 processingPart II: offers various algorithm designs for endmember extractionPart III: derives theory for supervised linear spectral mixture analysisPart IV: designs unsupervised methods for hyperspectral image analysisPart V: explores new concepts on hyperspectral information compressionParts VI & VII: develops techniques for hyperspectral signal coding and characterizationPart 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 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9780471690566
Descrizione libro Condizione: New. 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. Num Pages: 1164 pages, Illustrations. BIC Classification: RGW. Category: (P) Professional & Vocational. Dimension: 259 x 181 x 58. Weight in Grams: 2086. . 2013. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. Codice articolo V9780471690566
Descrizione libro Condizione: New. 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. Num Pages: 1164 pages, Illustrations. BIC Classification: RGW. Category: (P) Professional & Vocational. Dimension: 259 x 181 x 58. Weight in Grams: 2086. . 2013. 1st Edition. Hardcover. . . . . Codice articolo V9780471690566