Shivering greedy snakes, gradient-guided in wavelet domain
The convergence speed of snakes is increased with the switching step size of local minima search and they are incorporated with the local gradient information in the wavelet domain to provide extra speed of convergence to their final contours. This is important in model based compression applications using wavelet decomposition. The directional gradient information is extracted from the subbands provided for the three directions at each stage of the decomposition. The advantages of this approach include, increased speed of convergence due to the switching step size of search and due to the decreased number of pixels to be searched and decreased burden of calculations for pre-processing due to the decreased size of subbands and due to the decreased dimension of the Gaussian filters in the pre-processing stage.