A novel image smoothing model based on orientation information measure

In this paper, a novel image smoothing model based on orientation information measure with attempting to address the limitations of the adaptive p-Laplace (APL) model. Though the APL model can smooth images successfully, the staircase effect appears in the flat regions in the final results. Such a problem is closely associated with the poor adaptive scheme of the L^p norm of the APL model. In order to address this problem, we propose a new scheme in which the orientation information measure is adopted to detect edge. An efficient numerical schema is used for the implementation of the proposed model. Experimental results on image denoising demonstrate that the proposed model is capable of avoiding the staircase effect and preserving important boundary features efficiently while removing noise, and it has better performance than that of the APL model.