Mixed noise removal using hybrid fourth order mean curvature motion

Abstract

Image restoration is one of the fundamental problems in digital image processing. Although there exists a wide variety of methods for removing additive Gaussian noise, relatively few works tackle the problem of removing mixed noise type from images. In this work we utilize a new hybrid partial differential equation (PDE)model formixed noise corrupted images. By using a combinationmean curvature motion (MMC) and fourth order diffusion (FOD) PDEwe study a hybrid method to deal with mixture of Gaussian and impulse noises. The MMC-FOD hybrid model is implemented using an efficient essentially non-dissipative (ENoD) scheme for the MMC first to eliminate the impulse noise with a no dissipation. The FOD component is implemented using explicit finite differences scheme. Experimental results indicate that our scheme obtains optimal denoising with mixed noise scenarios and also outperforms related schemes in terms of signal to noise ratio improvement and structural similarity.