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Blind deconvolution of noisy blurred images via dispersion minimization

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2 Author(s)
C. Vural ; Dept. of Electr. & Comput. Eng., Wisconsin Univ., Madison, WI, USA ; W. A. Sethares

In linear image restoration, the point spread function of the degrading system is assumed known even though this information is usually not available in real applications. As a result, both blur identification and image restoration must be performed from the observed noisy blurred image. This paper presents a computationally simple linear adaptive finite impulse response filter for blind image deconvolution. This is essentially a two-dimensional version of the constant modulus algorithm that is well known in the field of blind equalization. The two-dimensional extension is shown capable of reconstructing noisy blurred images using partial a priori information about the true image and the point spread function. The method is applicable to minimum as well as mixed phase blurs. Experimental results are provided.

Published in:

Digital Signal Processing, 2002. DSP 2002. 2002 14th International Conference on  (Volume:2 )

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