Blind Deconvolution Using Modulated Inputs

Blind deconvolution using temporal predictability

A measure of temporal predictability is de-ned, and used for blind deconvolution of sound signals. The method is based on the observation that physical environments act as smoothing -lters, and therefore increase the predictability of signals. These smoothing e0ects can be reversed by a deconvolution -lter which minimises a measure of temporal predictability. This -lter is obtained as the close...

Blind identification of ARMA channels with periodically modulated inputs

Recent results have pointed out the importance of inducing cyclostationarity at the transmitter for blind identification of FIR communication channels. The present paper considers the blind identification problem of an ARMA(p; q) channel by exploiting the cyclostationarity induced at the transmitter through periodic encoding of the input. It is shown that causal and stable ARMA(p; q) channels c...

Blind image deconvolution using the Sylvester matrix

Blind image deconvolution refers to the process of determining both an exact image and the blurring function from its inexact image. This thesis presents a solution of the blind image deconvolution problem using polynomial computations. The proposed solution does not require prior knowledge of the blurring function or noise level. Blind image deconvolution is needed in many applications, such a...

Identifying Image Tampering Using Blind Deconvolution Techniques

Multichannel blind seismic deconvolution using dynamic programming

In this paper, we present an algorithm for multichannel blind deconvolution of seismic signals, which exploits lateral continuity of earth layers by dynamic programming approach. We assume that reflectors in consecutive channels, related to distinct layers, form continuous paths across channels. We introduce a quality measure for evaluating the quality of a continuous path, and iteratively appl...