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
On the Inverse Hough Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
A Review of Nonlinear Diffusion Filtering
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Stability and local feature enhancement of higher order nonlinear diffusion filtering
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
Anisotropic diffusion of multivalued images with applications to color filtering
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Fourth-order partial differential equations for noise removal
IEEE Transactions on Image Processing
A fast Hough transform for segment detection
IEEE Transactions on Image Processing
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Image processing algorithms are being intensively researched in the last decades. One of the most influential filtering tendencies is based on partial differential equations (PDE). Different kinds of modifications of classical linear process were already proposed. Most of them are based on non-linear or anisotropic process taking into consideration local descriptor of image structure. Main goal is to remove noise and simultaneously to decrease level of blurring important features (like edges). In this paper a new approach is presented, which introduces, into non-linear diffusion process, extra knowledge about geometric structures existing on an image. Algorithm scheme is proposed and results of numerical experiments are presented. Moreover, possibilities of algorithm application within cellular neural networks paradigm will be analysed.