The paper presents an high-resolution Remote Sensing image segmentation method, which uses distributions of local
binary patterns/contrasts (LBP/C) of Gabor texture features for measuring the similarity of adjacent image regions during
the segmentation process. The method and algorithmic is integrated into split-merge plus refinement framework. The
central rationale of the method is that automatically segmenting image into different regions corresponding to Gabor
texture feature. In the procedure for split-merge and refinement, segmentation is realized by comparing correlation
coefficient between different Gabor features LBP/C histogram of sub-regions. The image can be segmented into
different regions that frequently correspond to different land-use or other objects. Experimental results show that it is
effective to uses the Gabor texture features in high-resolution remote sensing image segmentation.
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