This article describes and analyzes the parallelization of the Anisotropic Nonlinear Diffusion (AND) for filtering 3D images. AND is one of the most powerful denoising techniques in the field of computer vision. This technique consists in resolving the equation of diffusion tightly coupled with a massive set of eigensystems. Denoising large 3D images in biomedicine and structural cellular biology by AND has a high computational cost. In this work, we propose a portable and efficient parallel implementation of AND based on a hybrid paradigm that combines (1)the message passing model and (2)the shared address space model. The proposed parallel implementation has been evaluated on a cluster of SMPs based on a UMA Uniform Memory access. The evaluation results show that the hybrid model is more suitable for this kind of platforms.