Date of Award
12-2009
Degree Type
Closed Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Dr. Michael Stewart - Chair
Second Advisor
Dr. Frank Hall
Third Advisor
Dr. Zhongshan Li
Abstract
The Kalman Filter has many applications in control and signal processing but may also be used to reconstruct a higher resolution image from a sequence of lower resolution images (or frames). If the sequence of low resolution frames is recorded by a moving camera or sensor, where the motion can be accurately modeled, then the Kalman filter may be used to update pixels within a higher resolution frame to achieve a more detailed result. This thesis outlines current methods of implementing this algorithm on a scene of interest and introduces possible improvements for the speed and efficiency of this method by use of block operations on the low resolution frames. The effects of noise on camera motion and various blur models are examined using experimental data to illustrate the differences between the methods discussed.
DOI
https://doi.org/10.57709/1192444
Recommended Citation
Dobson, William Keith, "Method for Improving the Efficiency of Image Super-Resolution Algorithms Based on Kalman Filters." Thesis, Georgia State University, 2009.
doi: https://doi.org/10.57709/1192444