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In many video imaging applications, it is of interest to enhance the resolution of the sensing device by resorting to software, rather than making expensive hardware modifications. This aim is realized in super-resolution processing, where an unaliased image (or sequence) is extracted from a sequence of lower resolution images. We have developed computationally efficient and statistically robust algorithms for performing this inversion. We have developed a comprehensive software package which implements our techniques and several other techniques.

Related Journal Publications

1. S. Farsiu, M. Elad, and P. Milanfar, “Video-to-Video Dynamic Superresolution for Grayscale and Color Sequences”, EURASIP Journal of Applied Signal Processing, Special Issue on Superresolution Imaging, Volume 2006, Article ID 61859, Pages 1-15.
   
2. D. Robinson, and P. Milanfar, “Statistical Performance Analysis of Super-resolution”, IEEE Transactions on Image Processing, Vol. 15, no. 6, pp. 1413-1428, June 2006.
3. S. Farsiu, M. Elad, and P. Milanfar, “Multi-Frame Demosaicing and Super-Resolution of Color Images”, IEEE Trans. on Image Processing, vol. 15, no. 1, pp. 141-159, January 2006.
4. S. Farsiu D. Robinson, M. Elad, and P. Milanfar, “Advances and Challenges in Super-Resolution”, Invited Paper, International Journal of Imaging Systems and Technology, Special Issue on High Resolution Image Reconstruction, vol. 14, no. 2, pp. 47-57, 2004.
5. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, “Fast and Robust Multi-frame Super-resolution”, IEEE Transactions on Image Processing, vol. 13, no. 10, pp. 1327-1344, October 2004.
6. N. Nguyen, P. Milanfar, G.H. Golub, “Efficient Generalized Cross-Validation with Applications to Parametric Image Restoration and Resolution Enhancement”, IEEE Transactions on Image Processing, vol. 10, no. 9, pp. 1299-1308, September 2001.
7. N. Nguyen, P. Milanfar, G.H. Golub, “A Computationally Efficient Image Superresolution Algorithm”, IEEE Transactions on Image Processing, vol. 10, no. 4, pp. 573-583, April 2001.

Related Conference Publications and Presentations

1. S. Farsiu, M. Elad, and P. Milanfar, “A Practical Approach to Super-Resolution”, Invited paper, Proc. of the SPIE Conf. on Visual Communications and Image Processing, San Jose, January 2006.
2. S. Farsiu, M. Elad, P. Milanfar, “Constrained, Globally Optimal, Multi-frame Motion Estimation”, Proc. of the 2005 IEEE Workshop on Statistical Signal Processing, Bordeaux, France, July 2005.
3. P. Milanfar, “Resolution and Its Enhancement in Imaging” (Extended abstract), Invited Talk, Optical Society of America Topical Meeting on Signal Recovery and Synthesis, Charlotte, North Carolina, June 2005.
4. D. Robinson, and P. Milanfar, “Statistical Performance Analysis of Superresolution Image Reconstruction”, Proceedings of the 38th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2004.
5. S. Farsiu, D. Robinson, M. Elad, and P Milanfar, “Dynamic Demosaicing and Color Super-Resolution of Video Sequences”, Proceedings of SPIE Conference on Image Reconstruction from Incomplete Data III - Volume 5562, October 2004.
6. S. Farsiu, M. Elad, P. Milanfar, “Multi-Frame Demosaicing and Super-Resolution from Under-Sampled Color Images”, Proceedings of the SPIE Conference on Computational Imaging, Jan. 18-22, 2004, San Jose, CA.
7. S. Farsiu, D. Robinson, M. Elad, P. Milanfar, “Robust Shift-and-Add Approach to Super-resolution”, Proceedings of the SPIE Annual Meeting, San Diego, CA, August 2003.
8. S. Farsiu, M. D. Robinson, M. Elad, P. Milanfar, “Fast Robust Superresolution”, Proceedings of the 2003 IEEE International Conference on Image Processing, Barcelona.