Title: Curvature driven diffusion coupled with shock for image enhancement/reconstruction

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.

DOI: 10.1504/IJSISE.2011.044541

International Journal of Signal and Imaging Systems Engineering, 2011 Vol.4 No.4, pp.238 - 247

Available online: 30 Dec 2011 *

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