High performance computing in remote sensing
著者
書誌事項
High performance computing in remote sensing
(Chapman & Hall/CRC computer and information science series / series editor, Sartaj Sahni)
Chapman & Hall, c2008
- : hbk
大学図書館所蔵 全4件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
Solutions for Time-Critical Remote Sensing Applications
The recent use of latest-generation sensors in airborne and satellite platforms is producing a nearly continual stream of high-dimensional data, which, in turn, is creating new processing challenges. To address the computational requirements of time-critical applications, researchers have begun incorporating high performance computing (HPC) models in remote sensing missions. High Performance Computing in Remote Sensing is one of the first volumes to explore state-of-the-art HPC techniques in the context of remote sensing problems. It focuses on the computational complexity of algorithms that are designed for parallel computing and processing.
A Diverse Collection of Parallel Computing Techniques and Architectures
The book first addresses key computing concepts and developments in remote sensing. It also covers application areas not necessarily related to remote sensing, such as multimedia and video processing. Each subsequent chapter illustrates a specific parallel computing paradigm, including multiprocessor (cluster-based) systems, large-scale and heterogeneous networks of computers, grid computing platforms, and specialized hardware architectures for remotely sensed data analysis and interpretation.
An Interdisciplinary Forum to Encourage Novel Ideas
The extensive reviews of current and future developments combined with thoughtful perspectives on the potential challenges of adapting HPC paradigms to remote sensing problems will undoubtedly foster collaboration and development among many fields.
目次
Preface. High Performance Computing Architectures for Remote Sensing Data Analysis: Overview and Case Study. Computer Architectures for Multimedia and Video Analysis. Parallel Implementation of the ORASIS Algorithm for Remote Sensing Data Analysis. Parallel Implementation of the Recursive Approximation of an Unsupervised Hierarchical Segmentation Algorithm. Computing for Analysis and Modeling of Hyperspectral Imagery. Parallel Implementation of Morphological Neural Networks for Hyperspectral Image Analysis. Parallel Wildland Fire Monitoring and Tracking Using Remotely Sensed Data. An Introduction to Grids for Remote Sensing Applications. Remote Sensing Grids: Architecture and Implementation. Open Grid Services for Envisat and Earth Observation Applications. Design and Implementation of a Grid Computing Environment for Remote Sensing. A Solutionware for Hyperspectral Image Processing and Analysis. AVIRIS and Related 21st-Century Imaging Spectrometers for Earth and Space Science. Remote Sensing and High Performance Reconfigurable Computing Systems. FPGA Design for Real-Time Implementation of Constrained Energy Minimization for Hyperspectral Target Detection. Real-Time Online Processing of Hyperspectral Imagery for Target Detection and Discrimination. Real-Time On-Board Hyperspectral Image Processing Using Programmable Graphics Hardware. Index.
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