Sciweavers

Share
DCC
2004
IEEE

Predicting Wavelet Coefficients Over Edges Using Estimates Based on Nonlinear Approximants

9 years 11 months ago
Predicting Wavelet Coefficients Over Edges Using Estimates Based on Nonlinear Approximants
It is well-known that wavelet transforms provide sparse decompositions over many types of image regions but not over image singularities/edges that manifest themselves along curves. It is now widely accepted that, on 2D piecewise smooth signals, wavelet compression performance is dominated by coefficients over edges. Research in this area has focused on two tracks, each suffering from issues related to translation invariance. Methods that directly model high order coefficient dependencies over edges have to combat aliasing issues, and new transforms that have been designed lose their full strength if they are not used in a translation invariant fashion. In this paper we combine these approaches and use translation invariant, overcomplete representations to predict wavelet edge coefficients.By starting with the lowest frequency band of an l level wavelet decomposition, we reliably estimate missing higher frequency coefficients over piecewise smooth signals. Unlike existing techniques, ...
Onur G. Guleryuz
Added 25 Dec 2009
Updated 25 Dec 2009
Type Conference
Year 2004
Where DCC
Authors Onur G. Guleryuz
Comments (0)
books