Anisotropic diffusion for Monte Carlo noise reduction
ACM Transactions on Graphics (TOG)
On the Incorporation of Time-delay Regularization into Curvature-based Diffusion
Journal of Mathematical Imaging and Vision
Non-negative sparse coding shrinkage for image denoising using normal inverse Gaussian density model
Image and Vision Computing
Two new nonlinear nonlocal diffusions for noise reduction
Journal of Mathematical Imaging and Vision
An unbiased implementation of regularization mechanisms
Image and Vision Computing
Two Enhanced Fourth Order Diffusion Models for Image Denoising
Journal of Mathematical Imaging and Vision
On a System of Adaptive Coupled PDEs for Image Restoration
Journal of Mathematical Imaging and Vision
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We present a class of time-delay anisotropic diffusion models for image restoration. These models lead to asymptotic states that are selected on the basis of a contrast parameter and bear some analogy with neural networks with Hebbian dynamical learning rules. Numerical examples show that these models are efficient in removing even high levels of noise, while allowing an accurate tracking of the edges