Motion blur disturbs - the influence of motion-blurred images in photogrammetry

Photogrammetric Record

Volumn 29, Issue 148, 2014, Pages 434-453

  Sieberth, T ^a   Wackrow, R ^a   Chandler, J H ^a  

^a LOUGHBOROUGH UNIVERSITY   (United Kingdom)

Author keywords

UAV; Automation; Blur; Bundle adjustment; Camera calibration; Image processing; Photogrammetry

Indexed keywords

ANTENNAS; AUTOMATION; CAMERAS; DATA HANDLING; IMAGE PROCESSING; PHOTOGRAMMETRY; UNMANNED AERIAL VEHICLES (UAV);

BLUR; BUNDLE ADJUSTMENTS; CAMERA CALIBRATION; DEGRADATION EFFECT; GROUND RESOLUTION; HIGH RESOLUTION CAMERA; MOTION BLURRED IMAGE; OPERATOR INTERVENTIONS;

IMAGE ACQUISITION;

EID: 84918593627     PISSN: 0031868X     EISSN: 14779730     Source Type: Journal    
DOI: 10.1111/phor.12082     Document Type: Article

References (29)

1. Boracchi, G., 2009. Estimating the 3D direction of a translating camera from a single motion-blurred image. Pattern Recognition Letters, 30(7): 671-681.
2. Boracchi, G., Caglioti, V. and Giusti, A., 2007. Ball position and motion reconstruction from blur in a single perspective image. 14th International Conference on Image Analysis and Processing ICIAP 2007, Modena, Italy. Pages 87-92.
3. Colombo, E. M., Kirschbaum, C. F. and Raitelli, M., 1987. Legibility of texts: the influence of blur. Lighting Research and Technology, 19(3): 61-71.
4. Eisenbeiss, H., 2009. UAV photogrammetry. Doctoral thesis 18515 ETH, Zurich, Switzerland. 235 pages.
5. Eisenbeiss, H., 2011. Tutorial on UAV-g: introduction. Presentation at UAV-g 2011, Zurich, Switzerland. http://www.geometh.ethz.ch/uav_g/tutorial/eisenbeiss_web [Accessed: 7th October 2014].
6. Eisenbeiss, H. and Sauerbier, M., 2011. Investigation of UAV systems and flight modes for photogrammetric applications. Photogrammetric Record, 26(136): 400-421.
7. Grenzdörffer, G., Niemeyer, F. and Schmidt, F., 2012. Development of four vision camera system for a micro-UAV. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 39(B1): 369-374.
8. Gülch, E., 2012. Photogrammetric measurements in fixed wing UAV imagery. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 39(B1): 381-386.
9. Johnson, C. A. and Casson, E. J., 1995. Effects of luminance, contrast, and blur on visual acuity. Optometry and Vision Science, 72(12): 864-869.
10. Joshi, N., Szeliski, R. and Kriegman, D. J., 2008. PSF estimation using sharp edge prediction. IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska, USA. 8 pages. http://dx.doi.org/10.1109/CVPR.2008.4587834
11. Kim, S. K. and Paik, J. K., 1998. Out-of-focus blur estimation and restoration for digital auto-focusing system. Electronics Letters, 34(12): 1217-1219.
12. Kraus, K., 2004. Photogrammetrie. Seventh edition. De Gruyter, Berlin, Germany. 516 pages.
13. Kraus, K., 2007. Photogrammetry - Geometry from Images and Laser Scans. Second edition. De Gruyter, Berlin, Germany. 459 pages.
14. Lelégard, L., Delaygue, E., Brédif, M. and Vallet, B., 2012. Detecting and correcting motion blur from images shot with channel-dependent exposure time. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 1(3): 341-346.
15. Liu, R., Li, Z. and Jia, J., 2008. Image partial blur detection and classification. IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, Alaska, USA. 8 pages. http://dx.doi.org/10.1109/CVPR.2008.4587465
16. Luhmann, T., 2014. Eccentricity in images of circular and spherical targets and its impact on spatial intersection. Photogrammetric Record, 29(148): 417-433.
17. Luhmann, T., Robson, S., Kyle, S. and Boehm, J., 2014. Close-Range Photogrammetry and 3D Imaging. Second edition. De Gruyter, Berlin, Germany. 684 pages.
18. Maison Nicéphore Niépce, 2013. http://www.niepce.org/pagus/pagus-inv.html [Accessed: 24th June 2013].
19. McCarthy, D. M. J., Chandler, J. H. and Palmeri, A., 2013. Monitoring dynamic structural tests using image deblurring techniques. Key Engineering Materials, Damage Assessment of Structures X, 569-570: 932-939.
20. Narvekar, N. D. and Karam, L. J., 2009. A no-reference perceptual image sharpness metric based on a cumulative probability of blur detection. International Workshop on Quality of Multimedia Experience, San Diego, California, USA. Pages 87-91.
21. Ong, E., Lin, W., Lu, Z., Yang, X., Yao, S., Pan, F., Jiang, L. and Moschetti, F., 2003. A no-reference quality metric for measuring image blur. Seventh International Symposium on Signal Processing and its Applications, Paris, France. 1: 469-472.
22. Pacey, R. and Fricker, P., 2005. Forward motion compensation (FMC) - is it the same in the digital imaging world? Photogrammetric Engineering & Remote Sensing, 71(11): 1241-1242.
23. Rahtu, E., Heikkilä, J., Ojansivu, V. and Ahonen, T., 2012. Local phase quantization for blur-insensitive image analysis. Image and Vision Computing, 30(8): 501-512.
24. Sachs, D., Nasiri, S. and Goehl, D., 2006. Image stabilization technology overview. http://www.invensense.com/jp/mems/gyro/documents/whitepapers/ImageStabilizationWhitepaper_051606.pdf [Accessed: 29th October 2013].
25. Shah, C. A. and Schickler, W., 2012. Automated blur detection and removal in airborne imaging systems using IMU data. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 39(B1): 321-323.
26. Shaked, D. and Tastl, I., 2005. Sharpness measure: towards automatic image enhancement. IEEE International Conference on Image Processing, Genoa, Italy. I: 937-940.
27. Shortis, M. R. and Seager, J. W., 2014. A practical target recognition system for close range photogrammetry. Photogrammetric Record, 29(147): 337-355.
28. Sieberth, T., Wackrow, R. and Chandler, J. H., 2013. Automatic isolation of blurred images from UAV image sequences. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(1/W2): 361-366.
29. Stiles, R. N., 1976. Frequency and displacement amplitude relations for normal hand tremor. Journal of Applied Physiology, 40(1): 44-54.