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Proceedings Paper

Seamless contiguity method for parallel segmentation of remote sensing image
Author(s): Geng Wang; Guanghui Wang; Mei Yu; Chengling Cui
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Paper Abstract

Seamless contiguity is the key technology for parallel segmentation of remote sensing data with large quantities. It can be effectively integrate fragments of the parallel processing into reasonable results for subsequent processes. There are numerous methods reported in the literature for seamless contiguity, such as establishing buffer, area boundary merging and data sewing. et. We proposed a new method which was also based on building buffers. The seamless contiguity processes we adopt are based on the principle: ensuring the accuracy of the boundary, ensuring the correctness of topology. Firstly, block number is computed based on data processing ability, unlike establishing buffer on both sides of block line, buffer is established just on the right side and underside of the line. Each block of data is segmented respectively and then gets the segmentation objects and their label value. Secondly, choose one block(called master block) and do stitching on the adjacent blocks(called slave block), process the rest of the block in sequence. Through the above processing, topological relationship and boundaries of master block are guaranteed. Thirdly, if the master block polygons boundaries intersect with buffer boundary and the slave blocks polygons boundaries intersect with block line, we adopt certain rules to merge and trade-offs them. Fourthly, check the topology and boundary in the buffer area. Finally, a set of experiments were conducted and prove the feasibility of this method. This novel seamless contiguity algorithm provides an applicable and practical solution for efficient segmentation of massive remote sensing image.

Paper Details

Date Published: 9 December 2015
PDF: 6 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 980820 (9 December 2015); doi: 10.1117/12.2209034
Show Author Affiliations
Geng Wang, China Univ. of Mining and Technology (China)
Guanghui Wang, Satellite Surveying and Mapping Application Ctr. (China)
Mei Yu, China Univ. of Mining and Technology (China)
Chengling Cui, China Univ. of Mining and Technology (China)


Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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