出版社:科学出版社
年代:2012
定价:60.0
光学遥感依靠开发分别拥有高空间和光谱分辨率的多光谱和超光谱图像。这些方式尽管对于大多的遥感任务是有用的,但是对于其有效利用性却有很大的挑战。本书介绍了当前国家最先进的算法,用来解决以下在分析光学遥感数据时遇到的关键性挑战,如预处理图像、储存和表示高维数据、模式分类和目标识别、高维图像的可视化等。
Introduction
Saurabh Prasad, Lori M. Bruce and Jocelyn Chanussot
Byperspeetral Data Compression Tradeoff
Emmanuel Christophe
Reconstructions from Compressive Random Projections
of Hyperspectral Imagery
James E. Fowler and Qian Du
Integrated Sensing and Processing for Hyperspeetrai Imagery
Robert Muise and Abhijit Mahalanobis
Color Science and Engineering for the Display of Remote
Sensing Images
Maya R. Gupta and Nasiha Hrustemovic
An Evaluation of Visualization Techniques for Remotely
Sensed Hyperspectral Imagery
Shangshu Cai, Robert Moorhead and Qian Du
A Divide-and-Conquer Paradigm for Hyperspectral Classification
and Target Recognition
Saurabh Prasad and Loft M. Bruce
The Evolution of the Morphological Profile: from Panchromatic
to Hyperspectral Images
Mauro DaUa Mura, Jon Atli Benediktsson, Jocelyn Chanussot
and Lorenzo Bruzzone
Decision Fusion of Multiple Classifiers for Vegetation Mapping
and Monitoring Applications by Means of Hyperspectral Data
Karoly Livius Bakos, Prashanth Reddy Marpu and Paolo Gamba
A Review of Kernel Methods in Remote Sensing Data Analysis
Luis G6mez-Chova, Jordi Mufioz-Maff, Valero Laparra,
Jestis Maio-L6pez and Gustavo Camps-Vails
Exploring Nonlinear Manifold Learning for Classification
of Hyperspectral Data
Melba M. Crawford, Li Ma and Wonkook Kim
Recent Developments in Endmember Extraction
and Spectral Unmixing
Antonio Plaza, Gabriel Martfn, Javier Plaza, Maciel Zortea
and Sergio Sanchez
Change Detection in VHR Multispectral Images:
Estimation and Reduction of Registration Noise Effects
Lorenzo Bruzzone, Silvia Marchesi and Francesca Bovolo
Effects of the Spatial Enhancement of Hyperspectral Images
on the Distribution of Spectral Classes
Andrea Garzelli and Luca Capobianco
Fusion of Optical and SAR Data for Seismic Vulnerability
Mapping of Buildings
Diego Polli and Fabio Dell'Acqua
《光学遥感信号处理与开发技术》(影印版)介绍了当前最先进的算法,用来解决在分析光学遥感数据时遇到的问题,如预处理图像、储存和表示高维数据、模式分类、目标识别以及高位图像的可视化等。《光学遥感信号处理与开发技术》(影印版)适合相关专业的高年级本科生及研究生阅读。
《光学遥感信号处理与开发技术》(影印版)是国外电子信息精品著作,共分14个部分,主要介绍了当前最先进的算法,用来解决在分析光学遥感数据时遇到的问题,如预处理图像、储存和表示高维数据、模式分类、目标识别以及高位图像的可视化等。