A Novel Graph Based Clustering Technique for Hybrid Segmentation of Multi-spectral Remotely Sensed Images
This paper proposes a novel unsupervised graph based clustering method for the purpose of hybrid segmentation of multi-spectral satellite images. In hybrid image segmentation framework, the source image is initially (over)segmented while preserving the fine image details. A region merging strategy has to be adopted next for further refinement. Here mean-shift (MS) based technique has been considered for initially segmenting the source image as it performs edge preserving smoothing beforehand hence eliminates noise. The objects found after this step are merged together in a low-level image feature space using the proposed graph based clustering algorithm. A graph topology combining k-nearest-neighbor (KNN) and minimum spanning tree has been considered on which the proposed iterative algorithm has been applied to eliminate the edges which span different clusters. It results in a set of connected components where each component represents a separate cluster. Comparison with two other hybrid segmentation techniques establishes the comparable accuracies of the proposed framework.
KeywordsImage Segmentation Graph Based Clustering Mean-Shift Hybrid Segmentation
Unable to display preview. Download preview PDF.
- 1.Aytekin, Ö., Ulusoy, İ., Halici, U.: Segmentation of high resolution satellite imagery based on mean shift algorithm and morphological operations. In: Proc. SPIE Eur. Remote Sens., pp. 747704–747704 (2009)Google Scholar
- 2.Banerjee, B., Surender, V.G., Buddhiraju, K.M.: Satellite image segmentation: A novel adaptive mean-shift clustering based approach. In: 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 4319–4322 (July 2012)Google Scholar
- 7.Li, Z., Wu, X.M., Chang, S.F.: Segmentation using superpixels: A bipartite graph partitioning approach. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 789–796. IEEE (2012)Google Scholar
- 8.Meinel, G., Neubert, M.: A comparison of segmentation programs for high resolution remote sensing data. International Archives of Photogrammetry and Remote Sensing 35(Pt. B), 1097–1105 (2004)Google Scholar