Blind Multichannel Deconvolution with Cascaded Kalman Filters

Modified Sparse Multichannel Blind Deconvolution

Blind Deconvolution with Sparse Priors on the Deconvolution Filters

In performing blind deconvolution to remove reverberation from speech signal, most acoustic deconvolution filters need a great many number of taps, and acoustic environments are often time-varying. Therefore, deconvolution filter coefficients should find their desired values with limited data, but conventional methods need lots of data to converge the coefficients. In this paper, we use sparse ...

Super-exponential methods for multichannel blind deconvolution

Multichannel blind deconvolution has received increasing attention during the last decade. Recently, Martone [3, 4] extended the super-exponential method proposed by Shalvi and Weinstein [1, 2] for single-channel blind deconvolution to multichannel blind deconvolution. However, the Martone extension suffers from two type of serious drawbacks. The objective of this paper is to obviate these draw...

Wavelet Estimation via Sparse Multichannel Blind Deconvolution

Blind Multichannel Image Deconvolution and Denoising

A multichannel blind deconvolution and image denoising method based on the Mutually Referenced Equalizers (MRE) approach is proposed. The main idea is to exploit the information diversity conveyed by the channels in order to estimate the degradations and the original signal. In the noiseless case a perfect restoration is obtained. To deal with the noisy case, a regularization term is introduced...