Title :
Signal recovery and wavelet reproducing kernels
Author :
Lu, Jian ; Healy, Dennis M., Jr. ; Weaver, John B.
Author_Institution :
Dept. of Math. & Comput. Sci., Dartmouth Coll., Hanover, NH, USA
fDate :
7/1/1994 12:00:00 AM
Abstract :
A class of signal recovery problems can be formulated as finding missing data at the finest scale of a discrete wavelet transform. A unique and stable recovery can be obtained by solving the regularized wavelet-reproducing equation. We show that this approach has close relations to unconstrained and constrained least-squares techniques and derive a family of regularizing operators adapted to the degrading operator. Experimental results present restored images using regularizing operators of this type
Keywords :
image reconstruction; least squares approximations; wavelet transforms; constrained least-squares techniques; degrading operator; discrete wavelet transform; missing data; regularizing operators; restored images; signal recovery; unconstrained least-squares; wavelet reproducing equation; Convolution; Cost function; Degradation; Discrete wavelet transforms; Image restoration; Integral equations; Kernel; Nonlinear filters; Signal restoration; Smoothing methods;
Journal_Title :
Signal Processing, IEEE Transactions on
