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http://dx.doi.org/10.7780/kjrs.2006.22.6.601

RAG-based Image Segmentation Using Multiple Windows  

Lee, Sang-Hoon (Kyungwon University)
Publication Information
Korean Journal of Remote Sensing / v.22, no.6, 2006 , pp. 601-612 More about this Journal
Abstract
This study proposes RAG (Region Adjancency Graph)-based image segmentation for large imagery in remote sensing. The proposed algorithm uses CN-chain linking for computational efficiency and multi-window operation of sliding structure for memory efficiency. Region-merging due to RAG is a process to find an edge of the best merge and update the graph according to the merge. The CN-chain linking constructs a chain of the closest neighbors and finds the edge for merging two adjacent regions. It makes the computation time increase as much as an exact multiple in the increasement of image size. An RNV (Regional Neighbor Vector) is used to update the RAG according to the change in image configuration due to merging at each step. The analysis of large images requires an enormous amount of computational memory. The proposed sliding multi-window operation with horizontal structure considerably the memory capacity required for the analysis and then make it possible to apply the RAG-based segmentation for very large images. In this study, the proposed algorithm has been extensively evaluated using simulated images and the results have shown its potentiality for the application of remotely-sensed imagery.
Keywords
image segmentation; RAG; CN-chain; sliding window; multi-window operation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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