Adaptive Anisotropic Diffusion for Image Denoising Based on Structure Tensor

Anisotropic diffusions based on gradient such as the Perona-Malik model indicate good performance in preserving the edges for image denoising. However, they often suffer so-called staircase effects and the loss of fine details. To overcome these drawbacks, a novel anisotropic diffusion model is proposed, whose diffusion coefficients are defined by the functions of both the determinant and the trace of the structure tensor of the image. Since the determinant and the trace of the structure tensor can well distinguish the smooth regions from the edges and corners, our proposed model can diffuse isotropic ally in the smooth regions, diffuses anisotropicly along the edges and confines the diffusion process in the corners. Some qualitative and quantitative experimental results demonstrate better performance in comparison with the cases of other anisotropic diffusion models.