Unsupervised colour image segmentation using dual-tree complex wavelet transform

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In this paper we present an effective unsupervised colour image segmentation algorithm which uses multiscale edge information and spatial colour content. The multiscale edge information is extracted using the dual-tree complex wavelet transform. Binary morphological operators are applied to the edge information to detect seed regions which are large enough to exclude boundary-only regions. The segmentation of homogeneous regions is obtained using region growing followed by region merging in the CIE L ∗ a ∗ b ∗ colour space. We also present an edge preserving smoothing filter as a pre-process for the algorithm. We compare our algorithm with state-of-the-art algorithms and show its superior performance.