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Multichannel blind image deconvolution using the Bussgang algorithm: spatial and multiresolution approaches

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4 Author(s)
G. Panci ; Dipt. di Scienza e Tecnica dell'Informazione e della Comunicazione, Univ. "La Sapienza" di Roma, Rome, Italy ; P. Campisi ; S. Colonnese ; G. Scarano

This work extends the Bussgang blind equalization algorithm to the multichannel case with application to image deconvolution problems. We address the restoration of images with poor spatial correlation as well as strongly correlated (natural) images. The spatial nonlinearity employed in the final estimation step of the Bussgang algorithm is developed according to the minimum mean square error criterion in the case of spatially uncorrelated images. For spatially correlated images, the nonlinearity design is rather conducted using a particular wavelet decomposition that, detecting lines, edges, and higher order structures, carries out a task analogous to those of the (preattentive) stage of the human visual system. Experimental results pertaining to restoration of motion blurred text images, out-of-focus spiky images, and blurred natural images are reported.

Published in:

IEEE Transactions on Image Processing  (Volume:12 ,  Issue: 11 )