Framework programming method for generic programming for data-intensive remote sensing image processing

Abstract

The invention relates to a data-intensive remote sensing image processing-oriented generic programmed framework programming method. The technical scheme comprises the following steps of 1, according to characteristics of large mass, complex data structure and the like of sensing image data, building a distributed remote sensing image model; 2, on the basis of remote data parallel processing algorithm analysis, modeling and abstracting a public computing mode which repeatedly appears, and building remote a sensing data processing algorithm-oriented parallel algorithm; and 3, packaging the parallel algorithm through a template mechanism to realize a generic programmed algorithm model. The method has the beneficial effects that a parallel programming mode is provided by remote sensing application algorithm, so that the parallel programming difficulty of a large amount of sensing data processing applications can be effectively reduced, the defect that the requirement on the programming ability of a domain expert in the traditional remote data processing is high is overcome, and wide application of parallel computing technology to large area even global massive remote data processing of global change, dynamic disaster monitoring and the like is greatly promoted.

Description

Technical field [0001] The invention relates to the field of remote sensing data processing, in particular to a framework programming method for generic programming for data-intensive remote sensing image processing. Background technique [0002] With the rapid development of remote sensing technology, remote sensing image data is increasing at a rate of terabytes per day. How to process massive amounts of data in real time, quickly and efficiently is an important challenge facing the current remote sensing data application. The rapid development of high-performance parallel computing technology based on distributed parallel clusters provides important technical means for data-intensive remote sensing image processing. Currently, multi-core cluster systems are gradually becoming the mainstream of parallel computing. This hybrid parallel system has a complex multi-layer parallel structure and an increasingly large system scale. Its parallel program development has multi-level par...

AI Technical Summary

Problems solved by technology

[0004] The technical problem of the present invention is: to overcome the existing data-intensive remote sensing data processing programming cumbersome, difficult, and low parallel efficiency defects, to provide a parallel programming model based on the algorithm Skeleton-oriented massive remote sensing data processing, the method will general Introduce type programming into the parallel development of remote sensing application algorithms. Based on the parallel computing characteristics of remote sensing algorithms and the analysis of parallel algorithm frameworks, Skeleton modeling and abstraction of massive remote sensing data processing methods are carried out, and a data-intensive remote sensing data processing algorithm is established. parallel programming paradigm

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