Blind single channel deconvolution using nonstationary signal processing

Blind single channel deconvolution using nonstationary signal processing

Single channel blind image deconvolution from radially symmetric blur kernels.

The multichannel exact blind image deconvolution theory tells us that exact recovery of unknown blur kernels is possible from multiple measurements of an identical scene through distinct blur channels. However, in many biological applications, there often exist technical difficulties in obtaining multiple distinct blur measurements, since the image content may vary for various reasons, includin...

Nonlinear and Nonstationary Signal Processing

An Adaptive Blind Deconvolution Signal Subspace Method

A blind deconvolution algorithm is introduced. The channel parameters are identi ed based on Maximum Likelihood (ML) criterion and the desired input is estimated using minimum variance estimation. Simulation results show the e cacy of our method. Its estimation error is usually less than other algorithms. Its rate of convergence is su ciently high and compete the others. Although, the algorithm...

On Information Maximization and Blind Signal Deconvolution

In the following paper we investigate two algorithms for blind signal deconvolution that has been proposed in the literature. We derive a clear interpretation of the information theoretic objective function in terms of signal processing and show that only one is appropriate to solve the deconvolution problem, while the other will only work if the unknown filter is constrained to be minimum phas...