Paper Info
Title
Extending anisotropic operators to recover smooth shapes
Abstract
Anisotropic differential operators are widely used in image enhancement processes. Recently, their property of smoothly extending functions to the whole image domain has begun to be exploited. Strong ellipticity of differential operators is a requirement that ensures existence of a unique solution. This condition is too restrictive for operators designed to extend image level sets: their own functionality implies that they should restrict to some vector field. The diffusion tensor that defines the diffusion operator links anisotropic processes with Riemmanian manifolds. In this context, degeneracy implies restricting diffusion to the varieties generated by the vector fields of positive eigenvalues, provided that an integrability condition is satisfied. We will use that any smooth vector field fulfills this integrability requirement to design line connection algorithms for contour completion. As application we present a segmenting strategy that assures convergent snakes whatever the geometry of the object to be modelled is.
Year
DOI
Venue
2005
10.1016/j.cviu.2004.12.001
Computer Vision and Image Understanding
Keywords
Field
DocType
functional extension,image level set,anisotropic differential operator,riemmanian manifolds,diffusion tensor,snake segmentation,smooth vector field,diffusion operator,smooth shape,contour completion,anisotropic process,differential operators,anisotropic operator,differential operator,whole image domain,vector field,image enhancement process,satisfiability,eigenvalues,level set
Topology,Vector field,Mathematical analysis,Edge detection,Level set,Differential operator,Degeneracy (mathematics),Operator (computer programming),Mathematics,Eigenvalues and eigenvectors,Manifold
Journal
Volume
Issue
ISSN
99
1
Computer Vision and Image Understanding
Citations 
PageRank 
References 
13
1.13
12
Authors
2
Name
Order
Citations
PageRank
Debora Gil1457.46
Petia Radeva21684153.53