PMID: 15376955Sep 21, 2004Paper

Super-resolution reconstruction of compressed video using transform-domain statistics

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Bahadir K GunturkRussell M Mersereau

Abstract

Considerable attention has been directed to the problem of producing high-resolution video and still images from multiple low-resolution images. This multiframe reconstruction, also known as super-resolution reconstruction, is beginning to be applied to compressed video. Super-resolution techniques that have been designed for raw (i.e., uncompressed) video may not be effective when applied to compressed video because they do not incorporate the compression process into their models. The compression process introduces quantization error, which is the dominant source of error in some cases. In this paper, we propose a stochastic framework where quantization information as well as other statistical information about additive noise and image prior can be utilized effectively.

References

Nov 1, 1989·Journal of the Optical Society of America. A, Optics and Image Science·H Stark, P Oskoui
Feb 6, 2008·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·A J Patti, Y Altunbasak
Jan 1, 1997·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·A J PattiA Murat Tekalp
Jan 1, 1996·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·R R Schultz, R L Stevenson
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Jan 1, 1993·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·S P Kim, W Y Su

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Citations

Jul 31, 2013·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Xinfeng ZhangWen Gao
Nov 10, 2007·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Deqing Sun, Wai-Kuen Cham
Mar 20, 2010·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Zhiwei XiongFeng Wu
Jan 14, 2016·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Jian ZhangWen Gao

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