Extracting High Quality Information From Under Sampled Images with Relative Motion Blur Using Non-blind Restoration Techniques: A Survey
Hendawy, W., Salama, G., Hussein, H., Hassanien, K. (2012). Extracting High Quality Information From Under Sampled Images with Relative Motion Blur Using Non-blind Restoration Techniques: A Survey. EKB Journal Management System, 8(8th International Conference on Electrical Engineering ICEENG 2012), 1-21. doi: 10.21608/iceeng.2012.30650
W. M. Hendawy; G. I. Salama; H. A. Hussein; K. I. Hassanien. "Extracting High Quality Information From Under Sampled Images with Relative Motion Blur Using Non-blind Restoration Techniques: A Survey". EKB Journal Management System, 8, 8th International Conference on Electrical Engineering ICEENG 2012, 2012, 1-21. doi: 10.21608/iceeng.2012.30650
Hendawy, W., Salama, G., Hussein, H., Hassanien, K. (2012). 'Extracting High Quality Information From Under Sampled Images with Relative Motion Blur Using Non-blind Restoration Techniques: A Survey', EKB Journal Management System, 8(8th International Conference on Electrical Engineering ICEENG 2012), pp. 1-21. doi: 10.21608/iceeng.2012.30650
Hendawy, W., Salama, G., Hussein, H., Hassanien, K. Extracting High Quality Information From Under Sampled Images with Relative Motion Blur Using Non-blind Restoration Techniques: A Survey. EKB Journal Management System, 2012; 8(8th International Conference on Electrical Engineering ICEENG 2012): 1-21. doi: 10.21608/iceeng.2012.30650

Extracting High Quality Information From Under Sampled Images with Relative Motion Blur Using Non-blind Restoration Techniques: A Survey

The International Conference on Electrical Engineering
Article 16, Volume 8, 8th International Conference on Electrical Engineering ICEENG 2012, May 2012, Page 1-21  XML PDF (1.27 MB)
Document Type: Original Article
DOI: 10.21608/iceeng.2012.30650
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Authors
W. M. Hendawy1; G. I. Salama2; H. A. Hussein2; K. I. Hassanien1
1Technical Research Department.
2Egyptian Armed Forces.
Abstract
Image degraded due motion blur is an ill-posed problem that still attracts many researchers to participate in solving such problem. The degraded image might suffer linear or nonlinear motion blur. It may also be due to the camera motion (spatial space invariant) or due to the motion of the target to be captured (spatially space variant). This paper focuses on images degraded due to linear motion blur due to the camera motion. A survey was done over several kernel estimation techniques such as Cepstral and Sinc function whom are classified under parameter estimation approach, and Fergus[1] and Krishnan[2] techniques who are classified under MAPh (Maximum A Posteriori over the kernel h) estimation approach. Experiments were applied over images samples suffering a synthetic blur and restored with several image restoration algorithms.
Keywords
Image restoration; motion blur and kernel estimation
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