A Remote Sensing Image Segmentation Method Based on Spectral and Structure Information Fusion

The focus of this paper is on the segmentation algorithm for the high resolution multispectral imagery to get regions which are roughly corresponding to land cover types. We propose the combination of spectral features and spatial features by Gabor filter banks and a variable mean shift clustering algorithm in high dimension is employed to achieve feature fusion. Some issues on the measure metric of different features and standilzation are discussed. The whole algorithm is evaluated on the synthetic texture image, which are cropped from a QuickBird image with typical land–cover types. Compared with fixed bandwidth Mean Shift segmentation algorithm, our method has better performance in distinguishing the different land cover types with similar spectral surface. ∗ E-mail: corresponding author :[email protected].