Motion Estimation Techniques in Super-Resolution Image Reconstruction. A Performance Evaluation
by
Dacil Barreto
University Institute of Applied Microelectronics, University of Las Palmas de Gran Canaria, Gran Canaria, Spain
Coauthors: Luis D. Alvarez and Javier Abad

For a number of problems involving image sequences, a good motion estimation is a crucial task. In particular, when obtaining a high resolution image or video sequence from a set of low resolution images [1], the quality of the estimated motion plays a critical role in the performance of the high resolution algorithm. In this paper, we evaluate two different non-parametric motion estimation techniques, one based on a block matching method [2] and the other based on the optical flow equation [3], to obtain sub-pixel displacements between frames. We will also consider the local quality of the displacement map to improve the high resolution estimations [4].

1. S.C. Park, M.K. Park and M.G. Kang, “Super-resolution Image Reconstruction: a Technical Overview”, IEEE Signal Processing Magazine, vol. 20, no. 3, 21-36, May 2003.

2. R.R. Schultz and R.L. Stevenson, “Extraction of High Resolution Frames from Video Sequences”, IEEE Transactions on Image Processing, vol. 5, no. 6, 996-1011, June 1996.

3. C.A. Segall, R. Molina, A.K. Katsaggelos and J. Mateos, “Bayesian Resolution Enhancement of Compressed Video”, IEEE Transactions on Image Processing, vol. 13, no. 7, 898-911, July 2004.

4. L.D. Alvarez, J. Mateos, R. Molina and A.K. Katsaggelos, “Observability and Predictibility in Super-Resolution”, Astronomical Data Analysis III, Sorrento, Naples, Italy, April 2004.

Date received: March 8, 2005