This paper discusses linear inverse filtering (deconvolution) from a stochastic signal processing point of view. A direct link between regularized deconvolution and minimum variance estimation is established, and exploited to propose a simple, one-pass optimization procedure. Experimental verification confirms the good results obtainable by the proposed approach.
Inverse filtering with signal-adaptive constraints
NARDUZZI, CLAUDIO
2005
Abstract
This paper discusses linear inverse filtering (deconvolution) from a stochastic signal processing point of view. A direct link between regularized deconvolution and minimum variance estimation is established, and exploited to propose a simple, one-pass optimization procedure. Experimental verification confirms the good results obtainable by the proposed approach.
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