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4 books on Hyperspectral Imagery [PDF]
November 06, 2024 | 19 |
These books are covering spectral resolution techniques, image calibration, data processing algorithms, material identification, environmental monitoring, agricultural analysis and mineral exploration using hyperspectral imagery.
1. Dimensionality Reduction of Hyperspectral Imagery
2023 by Arati Paul, Nabendu Chaki
This book offers insights into various types of dimensionality reduction (DR) methods and their efficacy in processing hyperspectral data. The authors begin by highlighting the crucial role of hyperspectral imagery (HSI) in remote sensing, emphasizing its high spectral resolution for improved material identification on the Earth's surface. They discuss potential challenges arising from the acquisition of HSI in numerous narrow and contiguous bands, forming a 3-dimensional image cube, often leading to information redundancy within the bands. The authors illustrate how managing a large number of bands introduces computational complexities, impacting efficiency. Subsequently, the book underscores the significance of DR as a crucial step in hyperspectral data analysis to address these challenges, providing readers with a comprehensive understanding of DR processes and their impact on effective HSI analysis.
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2. Advances in Hyperspectral Image Processing Techniques
2022 by Chein-I Chang
"Advances in Hyperspectral Image Processing Techniques" is a comprehensive and authoritative resource that delves into recent advancements in hyperspectral imaging (HSI) techniques, covering a spectrum of ideas that have emerged in the past few years. This work consolidates diverse research into a single reference, exploring applications across various disciplines. With an introductory chapter on HSI fundamentals and another on the extensive use of HSI techniques in satellite on-orbit and on-board processing, the book caters to readers engaged in these specific fields. The content, contributed by invited scholars, is organized into six parts, covering general theory, band selection techniques, compressive sensing, fusion of hyperspectral images, hyperspectral data unmixing, and hyperspectral image classification. With applications ranging from defense and intelligence to agriculture, forestry, environmental monitoring, food safety, and medical imaging, this book is an indispensable resource for industry professionals, researchers, academics, and graduate students in the field.
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3. Hyperspectral Imaging in Agriculture, Food and Environment
2018 by Alejandro Isabel Luna Maldonado, Humberto Rodriguez-Fuentes, Juan Antonio Vidales Contreras
This book explores the innovative facets and forthcoming trends of hyperspectral imaging in agriculture, food, and the environment. Addressing a range of topics, it delves into hyperspectral imaging and its applications in nondestructive quality assessment for fruits and vegetables, evaluating the quality and safety of meat, multimode hyperspectral imaging for food quality and safety, pattern recognition models for hyperspectral images, sequential classification of hyperspectral images, graph construction for hyperspectral data unmixing, target visualization methods for processing hyperspectral images, and soil contamination mapping with hyperspectral imagery. A valuable general reference, this book caters to students, professional engineers, and readers with an interest in the subject.
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4. Hyperspectral Imaging: Techniques for Spectral Detection and Classification
2013 by Chein-I Chang
"Hyperspectral Imaging: Techniques for Spectral Detection and Classification" originates from extensive research conducted at the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Focused on applications of statistical signal processing to hyperspectral imaging, the book advances non-literal (spectral) techniques for subpixel detection and mixed pixel classification. Serving as a unique resource, it acts as a comprehensive guide, offering a variety of techniques for hyperspectral data exploitation. Notably, the text delves into detailed discussions of known techniques, such as OSP (Orthogonal Subspace Projection) and CEM (Constrained Energy Minimization), developed previously in the RSSIPL. A self-contained reference, this book is valuable for researchers in academia and practitioners in government and industry seeking insights into hyperspectral imaging.
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How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. Dimensionality Reduction of Hyperspectral Imagery
2023 by Arati Paul, Nabendu Chaki
This book offers insights into various types of dimensionality reduction (DR) methods and their efficacy in processing hyperspectral data. The authors begin by highlighting the crucial role of hyperspectral imagery (HSI) in remote sensing, emphasizing its high spectral resolution for improved material identification on the Earth's surface. They discuss potential challenges arising from the acquisition of HSI in numerous narrow and contiguous bands, forming a 3-dimensional image cube, often leading to information redundancy within the bands. The authors illustrate how managing a large number of bands introduces computational complexities, impacting efficiency. Subsequently, the book underscores the significance of DR as a crucial step in hyperspectral data analysis to address these challenges, providing readers with a comprehensive understanding of DR processes and their impact on effective HSI analysis.
Download PDF
2. Advances in Hyperspectral Image Processing Techniques
2022 by Chein-I Chang
"Advances in Hyperspectral Image Processing Techniques" is a comprehensive and authoritative resource that delves into recent advancements in hyperspectral imaging (HSI) techniques, covering a spectrum of ideas that have emerged in the past few years. This work consolidates diverse research into a single reference, exploring applications across various disciplines. With an introductory chapter on HSI fundamentals and another on the extensive use of HSI techniques in satellite on-orbit and on-board processing, the book caters to readers engaged in these specific fields. The content, contributed by invited scholars, is organized into six parts, covering general theory, band selection techniques, compressive sensing, fusion of hyperspectral images, hyperspectral data unmixing, and hyperspectral image classification. With applications ranging from defense and intelligence to agriculture, forestry, environmental monitoring, food safety, and medical imaging, this book is an indispensable resource for industry professionals, researchers, academics, and graduate students in the field.
Download PDF
3. Hyperspectral Imaging in Agriculture, Food and Environment
2018 by Alejandro Isabel Luna Maldonado, Humberto Rodriguez-Fuentes, Juan Antonio Vidales Contreras
This book explores the innovative facets and forthcoming trends of hyperspectral imaging in agriculture, food, and the environment. Addressing a range of topics, it delves into hyperspectral imaging and its applications in nondestructive quality assessment for fruits and vegetables, evaluating the quality and safety of meat, multimode hyperspectral imaging for food quality and safety, pattern recognition models for hyperspectral images, sequential classification of hyperspectral images, graph construction for hyperspectral data unmixing, target visualization methods for processing hyperspectral images, and soil contamination mapping with hyperspectral imagery. A valuable general reference, this book caters to students, professional engineers, and readers with an interest in the subject.
Download PDF
4. Hyperspectral Imaging: Techniques for Spectral Detection and Classification
2013 by Chein-I Chang
"Hyperspectral Imaging: Techniques for Spectral Detection and Classification" originates from extensive research conducted at the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Focused on applications of statistical signal processing to hyperspectral imaging, the book advances non-literal (spectral) techniques for subpixel detection and mixed pixel classification. Serving as a unique resource, it acts as a comprehensive guide, offering a variety of techniques for hyperspectral data exploitation. Notably, the text delves into detailed discussions of known techniques, such as OSP (Orthogonal Subspace Projection) and CEM (Constrained Energy Minimization), developed previously in the RSSIPL. A self-contained reference, this book is valuable for researchers in academia and practitioners in government and industry seeking insights into hyperspectral imaging.
Download PDF
How to download PDF:
1. Install Google Books Downloader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
