Paper Info
Title
Novel Integro-Differential Equations In Image Processing And Its Applications
Abstract
Motivated by the hierarchical multiscale image representation of Tadmor et al.,(1) we propose a novel integro-differential equation (IDE) for a multiscale image representation. To this end, one integrates in inverse scale space a succession of refined, recursive 'slices' of the image, which are balanced by a typical curvature term at the finer scale. Although the original motivation came from a variational approach, the resulting IDE can be extended using standard techniques from PDE-based image processing. We use filtering, edge preserving smoothing to yield a family of modified IDE models with applications to image denoising and image deblurring problems. The IDE models depend on a user scaling function which is shown to dictate the BV* properties of the residual error. Numerical experiments demonstrate application of the IDE approach to denoising and deblurring. Finally, we also propose another novel IDE based on the (BV, L-1) decomposition. We present numerical results for this IDE and its variant and examine its properties.
Year
DOI
Venue
2010
10.1117/12.850779
COMPUTATIONAL IMAGING VIII
Keywords
Field
DocType
natural images, multiscale representation, total variation, denoising, deblurring, inverse scale, variational problem, integro-differential equation, energy decomposition
Image processing,Artificial intelligence,Image restoration,Edge-preserving smoothing,Computer vision,Differential equation,Mathematical optimization,Deblurring,Algorithm,Filter (signal processing),Integro-differential equation,Smoothing,Physics
Conference
Volume
ISSN
Citations 
7533
0277-786X
0
PageRank 
References 
Authors
0.34
2
2
Name
Order
Citations
PageRank
Prashant Athavale132.09
Eitan Tadmor2796163.63