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A novel region-merging approach guided by priority for high resolution image segmentation

Author:
Su, Tengfei
Source:
Remote sensing letters 2017 v.8 no.8 pp. 771-780
ISSN:
2150-7058
Subject:
algorithms, models, remote sensing, variance
Abstract:
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.
Agid:
5693596