Two-Dimensional Blind Deconvolution Using a Robust GCD Approach

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Two-Dimensional Blind Deconvolution Using a Robust GCD Approach
In this paper we examine the applicability of the previously proposed Greatest Common Divisor (GCD) method to blind image deconvolution. In this method, the desired image is approximated as the GCD of the two-dimensional polynomials corresponding to the ztransforms of two or more distorted and noisy versions of the same scene, assuming that the distortion lters are FIR and relatively co-prime. We justify the breakdown of two-dimensional GCD into one-dimensional Sylvester-type GCD algorithms, which lowers the computational complexity while maintaining the noise robustness. A way of determining the support size of the true image is also described. We also provide a solution to deblurring using the GCD method when only one blurred image is available. Experimental results are shown using both synthetically blurred images and real motion-blurred pictures.
S. U. Pillai, B. Liang
Added 26 Oct 2009
Updated 26 Oct 2009
Type Conference
Year 1997
Where ICIP
Authors S. U. Pillai, B. Liang
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