Spectral Spatial Classification Of Hyperspectral Remote Sensing Images
Download Spectral Spatial Classification Of Hyperspectral Remote Sensing Images full books in PDF, epub, and Kindle. Read online free Spectral Spatial Classification Of Hyperspectral Remote Sensing Images ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Spectral Spatial Classification of Hyperspectral Remote Sensing Images
Author | : Jon Atli Benediktsson,Pedram Ghamisi |
Publsiher | : Artech House |
Total Pages | : 280 |
Release | : 2015-09-01 |
Genre | : Technology & Engineering |
ISBN | : 9781608078134 |
Download Spectral Spatial Classification of Hyperspectral Remote Sensing Images Book in PDF, Epub and Kindle
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.
Spectral spatial Classification of Hyperspectral Remote Sensing Images
Author | : Jón Atli Benediktsson,Pedram Ghamisi |
Publsiher | : Artech House Publishers |
Total Pages | : 0 |
Release | : 2015 |
Genre | : Image processing |
ISBN | : 1608078124 |
Download Spectral spatial Classification of Hyperspectral Remote Sensing Images Book in PDF, Epub and Kindle
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.
Classification of Hyperspectral Remote Sensing Images
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 323 |
Release | : 2018-05 |
Genre | : Electronic Book |
ISBN | : 1642241768 |
Download Classification of Hyperspectral Remote Sensing Images Book in PDF, Epub and Kindle
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.
Deep Learning for Hyperspectral Image Analysis and Classification
Author | : Linmi Tao,Atif Mughees |
Publsiher | : Springer Nature |
Total Pages | : 207 |
Release | : 2021-02-20 |
Genre | : Computers |
ISBN | : 9789813344204 |
Download Deep Learning for Hyperspectral Image Analysis and Classification Book in PDF, Epub and Kindle
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 Image Processing
Author | : Liguo Wang,Chunhui Zhao |
Publsiher | : Springer |
Total Pages | : 315 |
Release | : 2015-07-15 |
Genre | : Technology & Engineering |
ISBN | : 9783662474563 |
Download Hyperspectral Image Processing Book in PDF, Epub and Kindle
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.
Hyperspectral Remote Sensing and Spectral Signature Applications
Author | : S. Rajendran |
Publsiher | : New India Publishing |
Total Pages | : 576 |
Release | : 2009 |
Genre | : Remote sensing |
ISBN | : 8189422340 |
Download Hyperspectral Remote Sensing and Spectral Signature Applications Book in PDF, Epub and Kindle
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.
Hyperspectral Remote Sensing
Author | : Prem Chandra Pandey,Prashant K. Srivastava,Heiko Balzter,Bimal Bhattacharya,George P. Petropoulos |
Publsiher | : Elsevier |
Total Pages | : 508 |
Release | : 2020-08-05 |
Genre | : Science |
ISBN | : 9780081028957 |
Download Hyperspectral Remote Sensing Book in PDF, Epub and Kindle
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
Processing and Analysis of Hyperspectral Data
Author | : Jie Chen,Yingying Song,Hengchao Li |
Publsiher | : BoD – Books on Demand |
Total Pages | : 137 |
Release | : 2020-01-22 |
Genre | : Science |
ISBN | : 9781789851090 |
Download Processing and Analysis of Hyperspectral Data Book in PDF, Epub and Kindle
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.