Super-resolution reconstruction of video sequences based on back-projection and motion estimation

Bandwidth limitation and service costs are important factors when dealing with mobile multimedia contents' fruition. Super-resolution reconstruction might be a relevant solution, since it allows for restoring the original spatial resolution from low-resolution compressed data. In this way, both content and service providers, not to tell the final users, are relieved from the burden of providing and supporting large multimedia data transfer. In the proposed work, the high-resolution video sequence is reconstructed through iterative processing of inter-frame information and interpolative techniques. Resolution enhancement is based on iterative update of the high-resolution image estimate through motion and scene change detection. The devised technique is derived from the work of Irani and Peleg [8]. The main contribution of the proposed approach consists in the generalization of the transformation model through the exploitation of local change. Results are encouraging and prove that the devised scheme outperforms alternative techniques.

[1]  Xuan Jing,et al.  An efficient three-step search algorithm for block motion estimation , 2004, IEEE Transactions on Multimedia.

[2]  Aggelos K. Katsaggelos A multiple input image restoration approach , 1990, J. Vis. Commun. Image Represent..

[3]  Robert L. Stevenson,et al.  Extraction of high-resolution frames from video sequences , 1996, IEEE Trans. Image Process..

[4]  Nirmal K. Bose,et al.  Recursive reconstruction of high resolution image from noisy undersampled multiframes , 1990, IEEE Trans. Acoust. Speech Signal Process..

[5]  Sebastiano Battiato,et al.  Improving image resolution by adaptive back-projection correction techniques , 2002, IEEE Trans. Consumer Electron..

[6]  Its'hak Dinstein,et al.  Local motion estimation and resolution enhancement of video sequences , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[7]  Shmuel Peleg,et al.  Improving image resolution using subpixel motion , 1987, Pattern Recognit. Lett..

[8]  Shmuel Peleg,et al.  Image sequence enhancement using sub-pixel displacements , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  H Stark,et al.  High-resolution image recovery from image-plane arrays, using convex projections. , 1989, Journal of the Optical Society of America. A, Optics and image science.

[10]  Michal Irani,et al.  Super resolution from image sequences , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[11]  Roger Y. Tsai,et al.  Multiframe image restoration and registration , 1984 .

[12]  Kiyoharu Aizawa,et al.  Acquisition of very high resolution images using stereo cameras , 1991, Other Conferences.

[13]  B R Frieden,et al.  Image reconstruction from multiple 1-D scans using filtered localized projection. , 1987, Applied optics.

[14]  Bing Zeng,et al.  A new three-step search algorithm for block motion estimation , 1994, IEEE Trans. Circuits Syst. Video Technol..

[15]  Michal Irani,et al.  Motion Analysis for Image Enhancement: Resolution, Occlusion, and Transparency , 1993, J. Vis. Commun. Image Represent..

[16]  A. Murat Tekalp,et al.  High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[17]  Aggelos K. Katsaggelos,et al.  Resolution enhancement of video sequences using motion compensation , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[18]  Aggelos K. Katsaggelos,et al.  Iterative algorithm for improving the resolution of video sequences , 1996, Other Conferences.

[19]  Michal Irani,et al.  Improving resolution by image registration , 1991, CVGIP Graph. Model. Image Process..