Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Representation of Image Structures via Scale Space Entropy Conditions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Encoding Visual Information Using Anisotropic Transformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Behavioral analysis of anisotropic diffusion in image processing
IEEE Transactions on Image Processing
Anisotropic diffusion of multivalued images with applications to color filtering
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Loss of information in images undergoing fine-to-coarse image transformations is analized by using an approach based on the theory of irreversible transformations. It is shown that entropy variation along scales can be used to characterize basic, low-level information and to gauge essential perceptual components of the image, such as shape and texture. The use of isotropic and anisotropic fine-to-coarse transformations of grey level images is discussed, and an extension of the approach to multi-valued images is proposed, where cross-interactions between the different colour channels are allowed.