Blind deconvolution of blurred images from multiple observations using the GCD algorithm

This paper suggests an approach for the 2-D blind deconvolution of more than two observations using the two-dimension greatest common divisor (GCD) algorithm. This approach benefits from the information in each observation at the same time instead of using only two observations at a time. The approa...

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Bibliographic Details
Main Authors: Hadhoud, M.M., Dessouky, M.I., El-Samie, F.E.A., El-Khamy, S.E.
Format: Conference Proceeding
Language:English
Subjects:
Data mining
Deconvolution
Degradation
Distortion measurement
Equations
Finite impulse response filter
Gaussian noise
Image restoration
Layout
Two dimensional displays
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Summary:This paper suggests an approach for the 2-D blind deconvolution of more than two observations using the two-dimension greatest common divisor (GCD) algorithm. This approach benefits from the information in each observation at the same time instead of using only two observations at a time. The approach depends on forming a combinational image from the available observations and performing the 2-D GCD on this image with all observations and then averaging the results to obtain the estimated image. Results are presented to illustrate the superiority of the proposed method.
DOI:10.1109/NRSC.2001.929229