Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image selective smoothing and edge detection by nonlinear diffusion
SIAM Journal on Numerical Analysis
Geometry-Driven Diffusion in Computer Vision
Geometry-Driven Diffusion in Computer Vision
Pattern Formation and Lattice Gas Automata
Pattern Formation and Lattice Gas Automata
A Review of Nonlinear Diffusion Filtering
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Multiscale Texture Enhancement
CAIP '95 Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns
Edge Based Probabilistic Relaxation for Sub-pixel Contour Extraction
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Lattice Boltzmann Models for Nonlinear Diffusion Filtering
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
A Lattice Boltzmann Model for Rotationally Invariant Dithering
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Parallel 3D Image Segmentation of Large Data Sets on a GPU Cluster
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
A lattice Boltzmann method for image denoising
IEEE Transactions on Image Processing
From tensor-driven diffusion to anisotropic wavelet shrinkage
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Application of Lattice Boltzmann Method to Image Filtering
Journal of Mathematical Imaging and Vision
Computers & Mathematics with Applications
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The lattice Boltzmann method has attracted more and more attention as an alternative numerical scheme to traditional numerical methods for solving partial differential equations and modeling physical systems. The idea of the lattice Boltzmann method is to construct a simplified discrete microscopic dynamics to simulate the macroscopic model described by the partial differential equations. The use of the lattice Boltzmann method has allowed the study of a broad class of systems that would have been difficult by other means. The advantage of the lattice Boltzmann method is that it provides easily implemented fully parallel algorithms and the capability of handling complicated boundaries. In this paper, we present two lattice Boltzmann models for nonlinear anisotropic diffusion of images. We show that image feature selective diffusion (smoothing) can be achieved by making the relaxation parameter in the lattice Boltzmann equation be image feature and direction dependent. The models naturally lead to the numerical algorithms that are easy toimplement. Experimental results on both synthetic and real images aredescribed.