Multispectral IKONOS image segmentation based on texture marker-controlled watershed algorithm

Segmentation has already been recognized as a valuable and complementary approach that performs a region-based rather than a point-based evaluation of high-resolution remotely sensed data. An approach to segmentation of multispectral IKONOS image based on texture marker-controlled watershed transform is presented. Primarily the texture and edge features are extracted from the response of log Gabor filtering. The texture features are obtained from the amplitude response, and phase congruency is introduced to detect invariant edge features. Then a method for multispectral IKONOS image segmentation based on band feature combination is demonstrated. After that an algorithm to combining texture with edge features is presented and used to implement the marker-controlled watershed segmentation. Finally empirical discrepancy is calculated to evaluate the segmentation results. It shows that the precision of right segmentation rate is up to 75% to 85%.

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