C.H. Morimoto, D. Koons, et al.
Image and Vision Computing
We consider the problem of detection of edges in an image by solving an anisotropic diffusion equation, which has the intrinsic property that low-contrast regions are smoothed and high-contrast ones are enhanced. Since wavelets are known to provide better representation of singularities (i.e., edges), a more efficient scheme than those suggested earlier for solving the diffusion equation is formulated in terms of wavelet expansions of the image. These expansions also provide a natural way of estimating the local contrast, and hence of implementing a space-varying parameterization of the diffusion equation for improved performance. Our method can be viewed as a wavelet counterpart of standard spectral methods for solving partial differential equations. ©1998 John Wiley & Sons, Inc.
C.H. Morimoto, D. Koons, et al.
Image and Vision Computing
Opher Etzion
DEBS 2007
Pavel Kisilev, Daniel Freedman, et al.
ICPR 2012
Benedikt Blumenstiel, Johannes Jakubik, et al.
NeurIPS 2023