Selective image smoothing via dyadic wavelet-based conduction equation

We propose a new dyadic wavelet-based conduction approach for selective image smoothing. In our approach, a nonlinear conductivity function is considered in the wavelet-based function decomposition and reconstruction process. Since the proposed approach does not require one to solve a PDE, it is therefore more efficient and accurate than the conventional nonlinear diffusion/conduction-based methods. Experimental results using both 1-D synthetic data and a real image demonstrated that the proposed method can efficiently remove noises and preserve real data.