Authors: P. Jidesh; Santhosh George
Addresses: Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Mangalore 575 025, India. ' Department of Mathematical and Computational Sciences, National Institute of Technology Karnataka, Mangalore 575 025, India
Abstract: Curvature driven diffusion is widely used for image denoising and inpainting. Among the curvature driven diffusion techniques Gauss Curvature Driven Diffusion (GCDD) became a prominent image denoising method due to its capability to retain some important structures with non zero curvatures, like curved edges, corners etc. Unlike many other non-linear diffusion techniques, the curvature driven diffusion hardly has any inverse diffusion characteristics. In this work we propose to introduce a shock term along with the GCDD term to enhance the edges while smoothing-out the noise. This technique will preserve some important structures and enhance them while denoising the image. The experiments clearly demonstrates the efficiency of the method.
Keywords: diffusion; image enhancement; shock filters; Gauss curvature; image reconstruction; image denoising; image processing.
International Journal of Signal and Imaging Systems Engineering, 2011 Vol.4 No.4, pp.238 - 247
Available online: 30 Dec 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article