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
Nonlinear Image Filtering with Edge and Corner Enhancement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
A multi-scale approach to nonuniform diffusion
CVGIP: Image Understanding
On the Representation of Image Structures via Scale Space Entropy Conditions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Entropy Production in Color Images
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Information measures in scale-spaces
IEEE Transactions on Information Theory
Behavioral analysis of anisotropic diffusion in image processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Generalized Spatio-Chromatic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Representation of Visual Information
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Using connected components to guide image understanding and segmentation
Machine Graphics & Vision International Journal
Image contrast enhancement via entropy production
Real-Time Imaging - Special issue on imaging in bioinformatics: Part III
Measuring perceptual contrast in digital images
Journal of Visual Communication and Image Representation
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The evolution of information in images undergoing fine-to-coarse anisotropic transformations is analyzed by using an approach based on the theory of irreversible transformations. In particular, we show that, when an anisotropic diffusion model is used, local variation of entropy production over space and scale provides the basis for a general method to extract relevant image features.