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...

Blind deconvolution is an ubiquitous non-linear inverse problem in applications like wireless communications and image processing. This problem is generally ill-posed since signal identifiability is a key concern, and there have been efforts to use sparse models for regularizing blind deconvolution to promote signal identifiability. Part I of this two-part paper establishes a measure theoretica...

Time-domain bidirectional deconvolution methods show great promise for overcoming the minimum-phase assumption in blind deconvolution of signals containing a mixed-phase wavelet, such as seismic data. However, usually one timedomain method is slow to converge (the slalom method) and the other one is sensitive to the initial point or preconditioner (the symmetric method). Claerbout proposed a lo...

Blind deconvolution is a common method for restoration of blurred text images, while binarization is employed to analyze and interpret the text semantics. In literature, these tasks are typically treated independently. This paper introduces a novel binarization driven blind deconvolution approach to couple both tasks in a common framework. The proposed method is derived as an energy minimizatio...

Nonstationary deconvolution has emerged as a tool for extracting the most realistic earth reflectivity from seismic traces, because of its adaptability to the characteristics of a given data set. Recently, deconvolution using the Gabor transform has been extended to yield deconvolution operators that are not only nonstationary in time, but also surface-consistent. We describe here a further ext...

We study the BV-α-Deconvolution model. It is a family of regularizations of the Barotropic Vorticity (BV) model that generalize the BV-α model and improve its accuracy. A both unconditionally stable and optimally convergent scheme for the BV-α-Deconvolution model is proposed and we show that it is O(α), where N is the deconvolution order, whereas the BV-α model is at most second order accurate....

Introduction: Hydronephrosis is one of the major causes of referring infants for nuclear medicine investigation. Renal dynamic study is the most reliable investigation for such children. However direct evaluation of renogram leads to generation of parameters that have no physiological interpretation. The configuration of renogram is very much dependent upon the rate at which radiopharmace...

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319 8.

In this paper we present a new multichannel blind deconvolution method based on so-called subspace technique that was originally proposed by Harikumar and Bresler. When at least two differently degraded images (channels) of the original scene are provided, the method is better conditioned than classical single channel ones. In comparison with earlier multichannel blind deconvolution techniques ...