System design and implementation of digital-image processing using computational grids

Authors:
Zhanfeng Shen;Jiancheng Luo;Chenghu Zhou;Guangyu Huang;Weifeng Ma;Dongping Ming
Affiliations:
State Key Laboratory of Resource and Environmental Information System (LREIS), Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Jia 11, ...;State Key Laboratory of Resource and Environmental Information System (LREIS), Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Jia 11, ...;State Key Laboratory of Resource and Environmental Information System (LREIS), Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Jia 11, ...;China University of Geosciences, Beijing 100083, PR China;Zhejiang University of Technology, Hangzhou 310014, PR China;State Key Laboratory of Resource and Environmental Information System (LREIS), Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Jia 11, ...
Venue:
Computers & Geosciences
Year:
2005

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Abstract

As a special type of digital image, remotely sensed images are playing increasingly important roles in our daily lives. Because of the enormous amounts of data involved, and the difficulties of data processing and transfer, an important issue for current computer and geo-science experts is developing internet technology to implement rapid remotely sensed image processing. Computational grids are able to solve this problem effectively. These networks of computer workstations enable the sharing of data and resources, and are used by computer experts to solve imbalances of network resources and lopsided usage. In China, computational grids combined with spatial-information-processing technology have formed a new technology: namely, spatial-information grids. In the field of remotely sensed images, spatial-information grids work more effectively for network computing, data processing, resource sharing, task cooperation and so on. This paper focuses mainly on the application of computational grids to digital-image processing. Firstly, we describe the architecture of digital-image processing on the basis of computational grids, its implementation is then discussed in detail with respect to the technology of middleware. The whole network-based intelligent image-processing system is evaluated on the basis of the experimental analysis of remotely sensed image-processing tasks; the results confirm the feasibility of the application of computational grids to digital-image processing.