An improved self-adaptive regularization method for mixed multiplicative and additive noise reduction

Abstract

The noise in micro focus X-ray images is complicated with low signal-to-noise-ratio (SNR) and can be described as mixed multiplicative and additive noise. Nevertheless, the present self-adaptive regularization methods for smoothing such mixed noise remain scarce. Thus, this paper proposes an improved self-adaptive regularization method to reduce the mixed multiplicative and additive noise in micro focus X-ray images. A novel scheme to adaptively select the regularization operator and regularization parameter based on local variance is presented, in which a p-Laplace function is used as the regularization operator with self-adaptive p and the regularization parameter is designed according to a barrier function. Experiment results demonstrate that the proposed method can achieve a better balance between noise-reducing and edge-preserving, which effectively improve the denoising quality.