Title :
Motion estimation for video coding based on sparse representation
Author :
Yanfei Shen ; Jintao Li ; Zhenmin Zhu
Author_Institution :
Inst. of Comput. Technol., Beijing, China
Abstract :
This paper describes a motion estimation algorithm based on sparse representation, which can be applied in video coding to reduce the temporal redundancy. The sparse coefficients are firstly calculated in support region by orthogonal matching pursuit (OMP) algorithm using the reference blocks as dictionary elements, and then these optimal sparse coefficients are utilized to predict the current block. To get the same prediction in decoder, the number of iterations in OMP is transmitted to decoder as side information. Simulation results show that gain up to 2.87dB in terms of the PSNR when compared with traditional translational motion estimation model.
Keywords :
compressed sensing; image matching; motion estimation; video coding; OMP algorithm; PSNR; decoder; dictionary elements; motion estimation algorithm; optimal sparse coefficients; orthogonal matching pursuit algorithm; reference blocks; same prediction; sparse representation; temporal redundancy; translational motion estimation model; video coding; Approximation methods; Dictionaries; Motion estimation; Prediction algorithms; Signal processing algorithms; Vectors; Video coding; motion estimation; sparse representation; video coding;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
DOI :
10.1109/ICASSP.2013.6637880