The lenses are important elements in optical imaging systems. However, lenses are liable to defects such as dusts and thus deteriorate their imaging quality. The polluted lens can be verified equivalent to a polluted random screen set against a clean lens. In our model, the defects on random screen are assumed poison-distribution, overlapped and the transmittance effect of each defect is multiplicative. In this thesis, we will apply Kalman filter to estimate the optical transfer function for a defected imaging system. The experiments are set up by the instruments including the video camera, capture card, and personal computer.
Kalman filter addresses an estimation problem defined by two models: the signal model and the observation model. Kalman filter was originally developed in the field of optimal estimation for application of controlling and tracking. Recently Kalman filter has been very often applied to the problems of image restoration. In this thesis, the signal model is obtained from a ratio of the defected and clean pictures in frequency domain. The observation model is built for an additive measurement noise from electronic sampling. Experimental results have demonstrated that the estimated optical transfer function is useful for image restoration.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0905105-174707 |
| Date | 05 September 2005 |
| Creators | Chiu, Hung-chin |
| Contributors | Chih-Peng Li, Ben-shung Chow, Rung-Hung Gau, Chin-hsing Chen |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0905105-174707 |
| Rights | not_available, Copyright information available at source archive |
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