摘要
Image segmentation, as a basic building block for many high-level image analysis problems, has attracted many research attentions over years. Existing approaches, however, are mainly focusing on the clustering analysis in the single channel information, i.e. , either in color or spatial space, which may lead to unsatisfactory segmentation performance. Considering the spatial and color spaces jointly, this paper propases a new hierarchical image segmentation algorithm, which alternately cluster.s the image regions in color and spatial spaces in a fine to coarse manner. Without losing the perceptual consistence, the proposed algorithm achieves the segmentation result using only very few number of colors according to user specification.
Image segmentation, as a basic building block for many high-level image analysis problems, has attracted many research attentions over years. Existing approaches, however, are mainly focusing on the clustering analysis in the single channel information, i.e. , either in color or spatial space, which may lead to unsatisfactory segmentation performance. Considering the spatial and color spaces jointly, this paper propases a new hierarchical image segmentation algorithm, which alternately cluster.s the image regions in color and spatial spaces in a fine to coarse manner. Without losing the perceptual consistence, the proposed algorithm achieves the segmentation result using only very few number of colors according to user specification.
