A new look to multichannel blind image deconvolution
IEEE Transactions on Image Processing
| Hi-index | 35.68 |
Developing fast and robust methods for identifying multiple FIR channels driven by an unknown common source is important for wireless communications, speech reverberation cancellation, and other applications. In this correspondence, we present a new method that exploits a minimum noise subspace (MNS). The MNS is computed from a set of channel output pairs that form a “tree”. The “tree” exploits, with minimum redundancy, the diversity among all channels. The MNS method is much more efficient in computation than a standard subspace method. The noise robustness of the MNS method is illustrated by simulation