The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

Xi Chen; Liqing Zhou

doi:10.1117/12.2207457

9 December 2015 The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

Xi Chen, Liqing Zhou

Proceedings Volume 9808, International Conference on Intelligent Earth Observing and Applications 2015; 98083T (2015) https://doi.org/10.1117/12.2207457
Event: International Conference on Intelligent Earth Observing and Applications, 2015, Guilin, China

Abstract

With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

Citation Download Citation

Xi Chen and Liqing Zhou "The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce", Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 98083T (9 December 2015); https://doi.org/10.1117/12.2207457

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