Segmentation of very high resolution imagery using spectral and structural information

Image Segmentation is an essential step for object-based analysis using very high resolution (VHR) images. A segmentation method by combined spectral and structural information was proposed in this paper for VHR multispectral images. The method consists of three steps. Structural information is first extracted and combined with spectral information to define pixel similarity. A region growing strategy using gradient image to determine seed points is then employed to produce initial segmentation results. A region merging step is finally performed to improve the initial results. Both visual inspection and quantitative measures are used to evaluate the performance of the proposed method. The experimental results of a Beijing area Quickbird image indicate that the proposed method achieves a better performance than existing morphological method and it is comparable with the widely used eCognition multi-resolution method.