MULTISCALE IMAGE REPRESENTATION USING NOVEL INTEGRO-DIFFERENTIAL EQUATIONS

被引:20
|
作者
Tadmor, Eitan [1 ,2 ]
Athavale, Prashant [2 ]
机构
[1] Univ Maryland, Dept Math, Inst Phys Sci & Technol, College Pk, MD 20742 USA
[2] Univ Maryland, Ctr Sci Computat & Math Modeling, College Pk, MD 20742 USA
关键词
natural images; multiscale representation; total variation; denoising; deblurring; inverse scale; variational problem; integro-differential equation; energy decomposition; EDGE-DETECTION; DECOMPOSITION;
D O I
10.3934/ipi.2009.3.693
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Motivated by the hierarchical multiscale image representation of Tadmor et. al., [25], 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 and tangential 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.
引用
收藏
页码:693 / 710
页数:18
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