Jitter camera: High resolution video from a low resolution detector

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 2, Issue , 2004, Pages

  Ben Ezra, Moshe ^a   Zomet, Assaf ^a   Nayar, Shree K ^a  

^a Columbia University ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONFIGURATION; CONSTANT VELOCITY; JITTER CAMERA; SPARTIAL RESOLUTION;

ALGORITHMS; CHARGE COUPLED DEVICES; COMPUTATIONAL METHODS; COMPUTER VISION; IMAGE ANALYSIS; JITTER; PARAMETER ESTIMATION;

CAMERAS;

EID: 5044234209     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. S. Baker and T. Kanade. Limits on super-resolution and how to break them. IEEE Trans. on Pattern Analysis and Machine Intelligence, 24(9):1167-1183, September 2002.
2. B. Bascle, A. Blake, and A. Zisserman. Motion deblurring and super-resolution from an image sequence. In European Conf. on Computer Vision, pages II:573-582, 1996.
3. M. Ben-Ezra, A. Zomet, and S.K. Nayar. Jitter camera: High resolution video from a low resolution detector. Technical Report CUCS-016-04, Department of Computer Science, Columbia University, April 2004.
4. J.R. Bergen, P. Anandan, K.J. Hanna, and R. Hingorani. Hierarchical model-based motion estimation. In European Conf. on Computer Vision, pages 237-252, 1992.
5. D. Capel and A. Zisserman. Super-resolution enhancement of text image sequences. In Int. Conf. Pattern Recognition, pages Vol I: 600-605, September 2000.
6. M.C. Chiang and T.E. Boult. Efficient super-resolution via image warping. Image and Vision Computing, 18(10):761-771, July 2000.
7. Pixera Corporation. Diractor, http://www.pixera.com/.
8. M. Elad and A. Feuer. Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images. IEEE Trans. Image Processing, 6(12):1646-1658, December 1997.
9. Physik Instrumente. M-111 micro translation stage, http://www. physikinstrumente.de/.
10. M. Irani and S. Peleg. Improving resolution by image registration. GMIP, 53:231-239, 1991.
11. Z. Lin and H.Y. Shum. Fundamental limits of reconstruction-based superresolution algorithms under local translation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 26(1):83-97, January 2004.
12. P. Meer, D. Mintz, D.Y. Kim, and A. Rosenfeld. Robust regression methods for computer vision: A review. International Journal of Computer Vision, 6(1):59-70, 1991.
13. Minolta. Dimage-a1, http://www.dpreview.com/reviews/minolta-dimagea1/.
14. A.J. Patti, M.I. Sezan, and A.M. Tekalp. Superresolution video reconstruction with arbitrary sampling lattices and nonzero aperture time. IEEE Trans. Image Processing, 6(8):1064-1076, August 1997.
15. A. Rav-Acha and S. Peleg. Restoration of multiple images with motion blur in different directions. In IEEE Workshop on Applications of Computer Vision, pages 22-28, 2000.
16. Point Grey Research. Dragonfly camera, http://www.ptgrey.com/.
17. R.R. Schultz and R.L. Stevenson. Extraction of high-resolution frames from video sequences. IEEE Trans. Image Processing, 5(6):996-1011, June 1996.
18. E. Shechtman, Y. Caspi, and M. Irani. Increasing space-time resolution in video. In European Conf. on Computer Vision, page I: 753 ff., 2002.
19. H. Shekarforoush and R. Chellappa. Data-driven multichannel superresolution with application to video sequences. Journal of the Optical Society of America, 16(3):481-492, March 1999.
20. E.P. Simoncelli. Modeling the joint statistics of images in the wavelet domain. SPIE, 3813:188-195, July 1999.