Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Biased anisotropic diffusion: a unified regularization and diffusion approach to edge detection
Image and Vision Computing - Special issue on the first ECCV 1990
Computerized Flow Field Analysis: Oriented Texture Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constrained Restoration and the Recovery of Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear Image Filtering with Edge and Corner Enhancement
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multi-scale approach to nonuniform diffusion
CVGIP: Image Understanding
Multiscale Texture Enhancement
CAIP '95 Proceedings of the 6th International Conference on Computer Analysis of Images and Patterns
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Anisotropic regularization PDE's (Partial Differential Equation) raised a strong interest in the field of image processing. The benefit of PDE-based regularization methods lies in the ability to smooth data in a nonlinear way, allowing the preservation of important image features (contours, corners or other discontinuities). In this article, a selective diffusion approach based on the framework of Extreme Physical Information theory is presented. It is shown that this particular framework leads to a particular regularization PDE which makes the integration of prior knowledge possible within the diffusion scheme. As a proof of feasibility, results of oriented pattern extractions are first presented on ad hoc images and second on a particular medical application: Tagged cardiac MRI (Magnetic Resonance Imaging) enhancement.