Segmentation of large-scale remotely sensed images on a Spark platform: A strategy for handling massive image tiles with the MapReduce model-Reference-Cited by-同舟云学术

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Segmentation of large-scale remotely sensed images on a Spark platform: A strategy for handling massive image tiles with the MapReduce model

Published:2020-04 Issue: Volume:162 Page:137-147
ISSN:0924-2716
Container-title:ISPRS Journal of Photogrammetry and Remote Sensing
language:en
Short-container-title:ISPRS Journal of Photogrammetry and Remote Sensing

Author:

Wang Ning,Chen Fang^ORCID,Yu Bo,Qin Yuchu

Funder

National Key R&D Program of China

National Natural Science Foundation of China

International Partnership Program of the Chinese Academy of Sciences

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference57 articles.

1. A parallel distributed-memory particle method enables acquisition-rate segmentation of large fluorescence microscopy images;Afshar;PLoS ONE,2016

2. Accelerating compute intensive medical imaging segmentation algorithms using hybrid CPU-GPU implementations;Alsmirat;Multimedia Tools and Applications,2017

3. Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation;Baatz,2000

4. Hierarchy in picture segmentation: a stepwise optimization approach;Beaulieu;IEEE Trans. Pattern Anal. Mach. Intell.,1989

5. Very high-resolution remote sensing: challenges and opportunities [Point of View];Benediktsson;Proc. IEEE,2012

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