Noise removal using smoothed normals and surface fitting

Authors:
M. Lysaker;S. Osher;Xue-Cheng Tai
Affiliations:
Dept. of Sci. Comput., Simula Res. Lab. AS, Norway;-;-
Venue:
IEEE Transactions on Image Processing
Year:
2004

Citing 0
Cited 38

Iterative Image Restoration Combining Total Variation Minimization and a Second-Order Functional

International Journal of Computer Vision
Inverse Scale Spaces for Nonlinear Regularization

Journal of Mathematical Imaging and Vision
Image restoration combining a total variational filter and a fourth-order filter

Journal of Visual Communication and Image Representation
Staircase effect alleviation by coupling gradient fidelity term

Image and Vision Computing
An extension of min/max flow framework

Image and Vision Computing
Convex Hodge Decomposition and Regularization of Image Flows

Journal of Mathematical Imaging and Vision
Support vector regression based image denoising

Image and Vision Computing
Accelerating total variation regularization for matrix-valued images on GPUs

Proceedings of the 6th ACM conference on Computing frontiers
Variational denoising of partly textured images

Journal of Visual Communication and Image Representation
An Improved LOT Model for Image Restoration

Journal of Mathematical Imaging and Vision
A Nonlinear Structure Tensor with the Diffusivity Matrix Composed of the Image Gradient

Journal of Mathematical Imaging and Vision
A Dual Formulation of the TV-Stokes Algorithm for Image Denoising

SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
An Anisotropic Fourth-Order Partial Differential Equation for Noise Removal

SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Anisotropic Smoothing Using Double Orientations

SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Image Denoising Using TV-Stokes Equation with an Orientation-Matching Minimization

SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
Efficient surface reconstruction from noisy data using regularized membrane potentials

IEEE Transactions on Image Processing
A fast optimization transfer algorithm for image inpainting in wavelet domains

IEEE Transactions on Image Processing
Ramp preserving Perona-Malik model

Signal Processing
An high order finite co-volume scheme for denoising using radial basis functions

SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
A TV-stokes denoising algorithm

SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
A new fourth-order equation model for image inpainting

FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
On high-order denoising models and fast algorithms for vector-valued images

IEEE Transactions on Image Processing
A two-step model for image denoising using a duality strategy and surface fitting

Journal of Computational and Applied Mathematics
Multigrid Algorithm for High Order Denoising

SIAM Journal on Imaging Sciences
Orientation-Matching Minimization for Image Denoising and Inpainting

International Journal of Computer Vision
An Anisotropic Fourth-Order Diffusion Filter for Image Noise Removal

International Journal of Computer Vision
A Modified TV-Stokes Model for Image Processing

SIAM Journal on Scientific Computing
Homotopy method for a mean curvature-based denoising model

Applied Numerical Mathematics
Augmented Lagrangian Method for Generalized TV-Stokes Model

Journal of Scientific Computing
Nonlocal surface fairing

SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
A New TV-Stokes Model with Augmented Lagrangian Method for Image Denoising and Deconvolution

Journal of Scientific Computing
An Inexact Alternating Directions Algorithm for Constrained Total Variation Regularized Compressive Sensing Problems

Journal of Mathematical Imaging and Vision
Image Denoising Using Mean Curvature of Image Surface

SIAM Journal on Imaging Sciences
A Variational Approach for Sharpening High Dimensional Images

SIAM Journal on Imaging Sciences
Exact Histogram Specification for Digital Images Using a Variational Approach

Journal of Mathematical Imaging and Vision
Anisotropic second and fourth order diffusion models based on Convolutional Virtual Electric Field for image denoising

Computers & Mathematics with Applications
Original Article: A new nonlocal total variation regularization algorithm for image denoising

Mathematics and Computers in Simulation
A coupled variational model for image denoising using a duality strategy and split Bregman

Multidimensional Systems and Signal Processing

Quantified Score

Hi-index	0.01

Visualization

Abstract

In this work, we use partial differential equation techniques to remove noise from digital images. The removal is done in two steps. We first use a total-variation filter to smooth the normal vectors of the level curves of a noise image. After this, we try to find a surface to fit the smoothed normal vectors. For each of these two stages, the problem is reduced to a nonlinear partial differential equation. Finite difference schemes are used to solve these equations. A broad range of numerical examples are given in the paper.