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Performance Bound of Position Estimation in Image Matching
Xu BS(徐保树); Shi ZL(史泽林)
Conference Name2010 International Conference on Remote Sensing (ICRS)
Conference DateOctober 5-6, 2010
Conference PlaceHangzhou, China
Author of SourceIEEE
Source PublicationProceedings of 2010 International Conference on Remote Sensing (ICRS)
Publication PlacePiscataway, NJ
Contribution Rank1
KeywordPerformance Prediction Image Matching Cramer-rao Lower Bound Fisher Information
AbstractPosition estimation in image matching is a fundamental step in computer vision and image processing. To deal with the problem of performance prediction, we formulate it under statistical parameter estimation aspect. The lower bound of position estimation variance is obtained based on Cramer-Rao lower bound (CRLB) theory. This paper analyses the impact of noise to 1-D signal matching, derives the lower bound of variance, and then extends it to 2-D image matching. Furthermore, we derive numerical expression that can be computed from observed data. Finally, we use Monte Carlo simulation method to verify the derived analytical expressions. Experimental results show that the derived CRLB is tight to simulation estimated variance. The CRLB can characterize the performance bound of position estimation in image matching.
Document Type会议论文
Corresponding AuthorXu BS(徐保树)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Graduate University of Chinese Academy of Sciences, Beijing, 100039, China
3.Key Laboratory of Optical-Electronics Information Processing, Chinese Academy of Sciences, Shenyang 110016, China
4.Key Laboratory of Image Understanding and Computer Vision, Liaoning Province, Shenyang 110016, China
Recommended Citation
GB/T 7714
Xu BS,Shi ZL. Performance Bound of Position Estimation in Image Matching[C]//IEEE. Piscataway, NJ:IEEE,2010:369-373.
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