Multichannel blind deconvolution of spatially misaligned images

Multichannel Blind Deconvolution of the Short-Exposure Astronomical Images

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 ...

Modified Sparse Multichannel Blind Deconvolution

Multichannel Blind Deconvolution of Seismic Signals

A new algorithm for simultaneous wavelet estimation and deconvolution of seismic reflection signals is given. To remove the inherent ambiguity in this blind deconvolution problem, we introduce relevant a priori information. Our major assumption is sparseness of the reflectivity, which corresponds to a layered earth model. This allows non-minimum phase wavelets to be recovered reliably and close...

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