Image denoising using non-local fuzzy means
Rushi Lan, Yicong Zhou, Yuan Yan Tang, C. L. Philip Chen · 2015
Due to the fact that the dissimilarity between the centered and other patches within an image dynamically changes in each denoising iteration, this paper proposes a new non-local image denoising algorithm called the non-local fuzzy means (NLFM). It considers the weights as fuzzy variables and adaptively update their values by solving an energy minimization problem. A new exponential parameter is introduced to the weights, offering a nonlinear mapping to enhance the NLFM's denoising performance. Two strategies are proposed to solve the energy minimization problem in different parameter settings. Experiments demonstrate that the NLFM outperforms several existing non-local means algorithms in terms of visual quality and quantitative measures.