DocumentCode :
2647921
Title :
Missing data estimation by separable deblurring
Author :
Qi, Hairong ; Snyder, Wesley E. ; Bilbro, Griff L.
Author_Institution :
Center for Adv. Comput. & Commun., North Carolina State Univ., Raleigh, NC, USA
fYear :
1998
fDate :
21-23 May 1998
Firstpage :
348
Lastpage :
353
Abstract :
Today´s technology allows butting a few sensor arrays to a high precision in order to capture a two-dimensional image of large area. The most serious defect caused by this butting technique is the gap between sub-arrays. This paper proposes an image restoration method to recover the missing data using the information of blur. We claim that by making a reasonable assumption that the blur in real world is usually Gaussian blur, we can take advantage of the separability property of Gaussian kernel to separate the deblurring process, and recover the missing data during the separated deblurring. We also prove that the problem is well-conditioned, and the algorithm we used is backward-stable. Experimental results are provided
Keywords :
Gaussian distribution; array signal processing; image restoration; 2D image; Gaussian blur; Gaussian kernel; backward-stable algorithm; butting; image restoration; missing data estimation; sensor arrays; separable deblurring; sub-array gap; well-conditioned problem; Biomedical equipment; Costs; Detectors; Image generation; Image restoration; Image sensors; Kernel; Medical services; Optical arrays; Sensor arrays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligence and Systems, 1998. Proceedings., IEEE International Joint Symposia on
Conference_Location :
Rockville, MD
Print_ISBN :
0-8186-8548-4
Type :
conf
DOI :
10.1109/IJSIS.1998.685473
Filename :
685473
Link To Document :
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