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A Multi‐granularity Parallel Model for Unified Remote Sensing Image Processing W eb S ervices
Author(s) -
Guo Wei,
Zhu Xinyan,
Hu Tao,
Fan LiWei
Publication year - 2012
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/j.1467-9671.2012.01367.x
Subject(s) - granularity , computer science , image processing , geospatial analysis , distributed computing , scheduling (production processes) , data processing , ask price , image (mathematics) , artificial intelligence , database , remote sensing , operating system , engineering , economy , economics , geology , operations management
The growth of the W eb has resulted in the W eb‐based sharing of distributed geospatial data and computational resources. The G eospatial P rocessing W eb ( G eo PW ) described here is a set of services that provide a wide array of geo‐processing utilities over the W eb and make geo‐processing functionalities easily accessible to users. High‐performance remote sensing image processing is an important component of the G eo PW . The design and implementation of high‐performance image processing are, at present, an actively pursued research topic. Researchers have proposed various parallel strategies for single image processing algorithm, based on a computer science approach to parallel processing. This article proposes a multi‐granularity parallel model for various remote sensing image processing algorithms. This model has four hierarchical interfaces that are labeled the R egion of Interest oriented ( ROI ‐oriented), D ecompose/ M erge, H ierarchical T ask C hain and D ynamic T ask interfaces or sub‐models. In addition, interfaces, definitions, parallel task scheduling and fault‐tolerance mechanisms are described in detail. Based on the model and methods, we propose an open‐source online platform named O pen RS ‐ C loud. A number of parallel algorithms were uniformly and efficiently developed, thus certifying the validity of the multi‐granularity parallel model for unified remote sensing image processing web services.