A greatest common divisor approach to blind super-resolution reconstruction of images

• Published in: Journal of modern optics Vol. 53; no. 8; pp. 1027 - 1039
• Main Authors: EL-Khamy, S. E., Hadhoud, M. M., Dessouky, M. I., Salam, B. M., Abd El-Samie, F. E.
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis Group 20.05.2006; Taylor & Francis
• Subjects: Exact sciences and technology; Fundamental areas of phenomenology (including applications); Image reconstruction; tomography; Imaging and optical processing; Optics; Physics; Signal-to-noise ratio; Image resolution; Algorithms; Superresolution; Image reconstruction
• ISSN: 0950-0340; 1362-3044
• DOI: 10.1080/09500340500445065

An algorithm for blind super-resolution reconstruction of a single image from multiple degraded observations is developed. The algorithm depends on estimating the 2D greatest common divisor (GCD) between each observation and a combinational image generated by a weighted averaging process of the available observations. The purpose of generating this combinational image is to obtain a new image with a higher signal to noise ratio, and a blurring operator that is co-prime with all the blurring operators of the available observations. The 2D GCD is then estimated between the new image and each observation and thus the effect of noise on the estimation process is reduced. The results of each 2D GCD process are fused to form a single reconstructed image, which is then interpolated subject to local regularization to form a high-resolution (HR) image. Results show that the proposed algorithm succeeds in estimating an HR image from noisy blurred observations in the case of relatively co-prime unknown blurring operators.