Comparison of PDE-based nonlinear anisotropic diffusion techniques for image denoising

Sisira K. Weeratunga; Chandrika Kamath

doi:10.1117/12.477744

28 May 2003 Comparison of PDE-based non-linear anistropic diffusion techniques for image denoising

Sisira K. Weeratunga, Chandrika Kamath

Proceedings Volume 5014, Image Processing: Algorithms and Systems II; (2003) https://doi.org/10.1117/12.477744
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

PDE-based, non-linear diffusion techniques are an effective way to denoise images.In a previous study, we investigated the effects of different parameters in the implementation of isotropic, non-linear diffusion. Using synthetic and real images, we showed that for images corrupted with additive Gaussian noise, such methods are quite effective, leading to lower mean-squared-error values in comparison with spatial filters and wavelet-based approaches. In this paper, we extend this work to include anisotropic diffusion, where the diffusivity is a tensor valued function which can be adapted to local edge orientation. This allows smoothing along the edges, but not perpendicular to it. We consider several anisotropic diffusivity functions as well as approaches for discretizing the diffusion operator that minimize the mesh orientation effects. We investigate how these tensor-valued diffusivity functions compare in image quality, ease of use, and computational costs relative to simple spatial filters, the more complex bilateral filters, wavelet-based methods, and isotropic non-linear diffusion based techniques.

Citation Download Citation

Sisira K. Weeratunga and Chandrika Kamath "Comparison of PDE-based non-linear anistropic diffusion techniques for image denoising", Proc. SPIE 5014, Image Processing: Algorithms and Systems II, (28 May 2003); https://doi.org/10.1117/12.477744

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