Title :
Occam filters for stochastic sources with application to digital images
Author :
Natarajan, Balas ; Konstantinides, Konstantinos ; Herley, Cormac
Author_Institution :
Hewlett-Packard Co., Palo Alto, CA, USA
fDate :
5/1/1998 12:00:00 AM
Abstract :
An Occam filter employs lossy data compression to separate signal from noise. Previously, it was shown that Occam filters can filter random noise from deterministic signals. Here, we show that Occam filters can also separate two stochastic sources, depending on their relative compressibility. We also compare the performance of Occam filters and wavelet-based denoising on digital images
Keywords :
Gaussian noise; data compression; filtering theory; image coding; rate distortion theory; stochastic processes; transform coding; wavelet transforms; Gaussian noise; Occam filters; SVD; deterministic signals; digital images; lossy data compression; random noise filtering; rate distortion theory; stochastic sources; wavelet-based denoising; Adaptive signal processing; Convergence; Digital filters; Digital images; Nonlinear filters; Predictive models; Signal processing; Signal processing algorithms; Stochastic processes; Wiener filter;
Journal_Title :
Signal Processing, IEEE Transactions on
