An edge fusion scheme for image denoising based on anisotropic diffusion models

Image information are classified as smooth regions, edges, corners and isolated noises.A reasonable diffusion tensor is defined to conduct the adaptive diffusion.An improved anisotropic diffusion denoising model for image enhancement is proposed.An edge fusion scheme is posed to preserve edges after denoising.Every mode of edge fusion scheme can preserve more edges than single denoising method. In this paper, we propose an enhanced anisotropic diffusion model. The improved model can classify finely image information as smooth regions, edges, corners and isolated noises by characteristic parameters and gradient variance parameter. And for different image information the eigenvalues of diffusion tensor are designed to conduct adaptive diffusion. Moreover, an edge fusion scheme is posed to preserve edges after denoising by combing different denoising and edge detection methods. Firstly, different denoising methods are applied for noisy image to obtain denoised images, and the best method among them is selected as main method. Then edge images of denoised images are obtained by edge detection methods. Finally, by fusing edge images together more integrated edges can be achieved to replace edges of denoised image obtained by main method. The experimental results show the proposed model can denoise meanwhile preserve edges and corners, and the edge fusion scheme is accurate and effective.