期刊
REMOTE SENSING LETTERS
卷 8, 期 8, 页码 771-780出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/2150704X.2017.1320441
关键词
-
资金
- National Natural Science Foundation of China [51569018]
In order to improve the segmentation accuracy for high resolution remote sensing image, merging priority is modeled and used to guide merging process. Within-segment spectral variance and inter-segment edge strength are exploited for model construction. In the proposed approach, the segment with the lowest model value is prioritized for processing. Local-mutual-best-fitting rule is then used to find the appropriate neighbor of the segment under processing. Two scenes of GF-2 multi-spectral images were adopted for algorithm validation. The results indicated that the proposed method outperformed some competitive approaches.
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