Restoration of spatially varying blurred images using multiple model-based extended Kalman filters
Image restoration based upon unrealistic homogeneous image and blur models can result in highly inaccurate estimates with excessive ringing. Thus, it is important at each pixel location to restore the image using the particular image and blur parameters characteristic of the immediate local neighbor...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 4(1995), 4 vom: 15., Seite 520-3 |
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| Weitere Verfasser: | , |
| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
1995
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Zusammenfassung: | Image restoration based upon unrealistic homogeneous image and blur models can result in highly inaccurate estimates with excessive ringing. Thus, it is important at each pixel location to restore the image using the particular image and blur parameters characteristic of the immediate local neighborhood. Toward this goal, a multiple model extended Kalman filters (EKF) procedure was developed and tested for spatially varying parameterized blurs. Results show this procedure to be very useful for restoring representative images with significant simulated variations of the blur parameter |
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| Beschreibung: | Date Completed 02.10.2012 Date Revised 21.02.2008 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1941-0042 |