Most existing methods of semi-supervised clustering introduce supervision from outside, e.g., manually label some data samples or introduce constrains into clustering results. Thi...
There are many challenges associated with the integration of synthetic and real imagery. One particularly difficult problem is the automatic extraction of salient parameters of na...
We show that the complexity of the recently introduced medoid-shift algorithm in clustering N points is O(N2 ), with a small constant, if the underlying distance is Euclidean. This...
The standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth...
Image decomposition consists of splitting an image into two or more components. One component is piecewise smooth and models object shapes. Another component consists of the textu...