Motion dependent spatiotemporal smoothing for noise reduction in very dim light image sequences

Proceedings - International Conference on Pattern Recognition

Volumn 3, Issue , 2006, Pages 954-959

  Malm, Henrik ^a   Warrant, Eric ^a  

^a LUND UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMALS; CAMERAS; MOTION PLANNING; NOISE ABATEMENT; THREE DIMENSIONAL;

GAUSSIAN SHAPED SMOOTHING KERNELS; IMAGE SEQUENCES; VIDEO SEQUENCES; VISUAL SYSTEMS;

IMAGE ANALYSIS;

EID: 34147142880     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2006.813     Document Type: Conference Paper

References (25)

1. G. Arce. Multistage order statistic filters for image sequence processing. IEEE Tran. Singal Proc., 39(5):1146-1163, May 1991.
2. K. Boo and B. Bose. A motion-compensated spatio-temporal filter for image sequences with signal-dependent noise. IEEE Tran. Circuits Sys. Video Tech., 8(3):287-298, June 1998.
3. J. Boyce. Noice reduction of image sequences using adaptive motion compensated frame averaging. In Proc. IEEE Int. Conf. Acoust. Speech. Signal. Proc., volume 3, pages 461-464, San Francisco, CA, March 1992.
4. J. Brailean, R. Kleihorst, S. Efstratiadis, A. Katsaggelos, and R. Lagendijk. Noise reduction filters for dynamic image sequences: A review. Proc. IEEE, 83(9):1272-1289, September 1995 1995.
5. A. Bruhn, J. Wieckert, and C. Schnörr. Lucas/kanade meets horn/schunk: Combining local and global optic flow methods. Int. J. Computer Vision, 61(3):211-231, 2005.
6. R. Dugad and N. Ahuja. Video denoising by combining kalman and wiener estimates. In Proc. Int. Conf. Image Proc., volume 4, pages 152-156, Kobe, Japan, October 1999.
7. R. Gonzalez and R. Woods. Digital Image Processing. Addison-Wesley, 1992.
8. G. Granlund and H. Knutsson. Signal Processing for Computer Vision. Kluwer, 1995.
9. H. Haussecker and H. Spies. Handbook of Computer Vision and Applications, volume 2, chapter Motion, pages 125-151. Academic Press, 1999.
10. B. Horn. Robot Vision. MIT Press, 1986.
11. B. Jähne. Spatio-temporal image processing. Springer, 1993.
12. D. Kalivas and A. Sawchuk. Motion compensated enhancement of noisy image sequences. In Proc. IEEE Int. Conf. Acoust. Speech. Signal. Proc., pages 2121-2124, Alburquerque, NM, April 1990.
13. J. Kim and J. Woods. Spatio-temporal adaptive 3-d kalman filter for video. IEEE Tran. Image Proc., 6(3):414-424, March 1997.
14. R. Kleihorst, R. Lagendijk, and J. Biemond. Noise reduction on severly corrupted image sequences. In Proc. IEEE Int. Conf. Acoust. Speech. Signal. Proc., volume 5, pages 293-296, Minneapolis, MN, April 1993.
15. R. Kleihorst, R. Lagendijk, and J. Biemond. Noise reduction of image sequences using motion compensation and signal decomposition. IEEE Tran. Image Proc., 4(3):274-284, March 1995.
16. S.-J. Ko and T. Forest. Image sequence enhancement based on adaptive symmetric order statistics. IEEE Tran. Circ. Sys. II: Analog and Digtal Signal Proc., 40(8):504-509, August 1993.
17. S.-W. Lee, V. Maik, J. Jang, J. Shin, and J. Paik. Noise-adaptive spatio-temporal filter for real-time noise removal in low light level images. IEEE Tran. Consumer Electronics, 51(2):648-653, May 2005.
18. D. Martinez and J. Lim. Implicit motion compensated noise reduction of motion video signals. In Proc. IEEE Int. Conf. Acoust. Speech. Signal. Proc., pages 375-378, Tampa, FL, 1985.
19. K. Miyata and A. Taguchi. Spatio-temporal seperable data-dependent weighted average filtering for restoration of the image sequences. In Proc. IEEE Int. Conf. Acoust. Speech. Signal. Proc., volume 4, pages 3696-3699, Alburquerque, NM, May 2002.
20. M. Sezan, M. Özkan, and S. Fogel. Temporally adaptive filtering of noisy image sequences. In Proc. IEEE Int. Conf. Acoust. Speech. Signal. Proc., volume 4, pages 2429-2432, Toronto, Canada, May 1991.
21. H. Spies and H. Scharr. Accurate optical flow in noisy image sequences. In Proc. Int. Conf. Computer Vision, Vancouver, 2001.
22. C. Stauffer and W. Crimson. Adaptive background mixture models for real-time tracking. In Proc. IEEE Conf. Computer Vision Pattern Recog., volume 2, pages 246-252, Fort Collins, CO, June 1999.
23. D. Uttenweiler, C. Weber, B. Jähne, R. Fink, and H. Scharr. Spatiotemporal anisotropic diffusion filtering to improve signal-to-noise ratios and object restoration in fluorescence microscopic image sequences. J. of Biomedical Optics, 8(1):40-47, 2003.
24. E. Warrant. Seeing better at night: life style, eye design and the optimum strategy of spatial and temporal summation. Vision Research, 39:1611-1630, 1999.
25. M. Özkan, M. Sezan, and A. Tekalp. Adaptive motion-compensated filtering of noisy image sequences. IEEE Tran. Circuits Sys. Video Tech., 3(4):277-290, August 1993.