Blind deconvolution of noisy blurred images via dispersion minimization
Cabir Vural, William A. Sethares · 2003
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.