PDE-Based De-Noising Approach for Efficient Noise Reduction with Edge Preservation in Digital Image Processing

Anisotropic diffusion has widely been applied as a mechanism for intra region smoothing of images. The results of anisotropic diffusion can be used to obtain an enhanced image or as a precursor to higher-level processing such as shape description, edge detection, image segmentation and object identification and tracking, Although attractive in terms of edge localization and the ability to control scale, anisotropic diffusion may lead to the creation of false edges and false regions, among other ill effects. In this paper, the MMSE-based filtering performed on the finest scale, the optimized anisotropic diffusion model and the anisotropic diffusion is performed on the filtered scalespace. This research work is proposed an improved nonlinear PDE-based de-noising algorithm to achieve efficient noise reduction with edge preservation due to the construction of the wavelet-based linear scale-space.