Title :
New method robust video coding based on compressive sensing
Author :
Vahdat Kazemi;Hadi Seyedarabi;Ali Aghagolzadeh
Author_Institution :
Faculty of Electrical and Computer Engineering, University of Tabriz, Iran
Abstract :
Compressed sensing theory (Compressed Sensing, CS) can break through the Nyquist sampling theorem limit for efficient, high-precision sampling and reconstruction of signals. It is a new signal acquisition and processing theory which developed only in recent years. Main idea of this theory use sparsity or compressibility of signals, reconstruct the signals accurately or approximately through non-related measurement of sampling data in low dimension. Compressed sensing theory provides a new way of thinking to signal processing, it has gain wild attention from is proposed, many research institutions and researchers have conducted in depth research. In this article we proposed a robust method video coding based on Compressive sampling matching pursuit (CoSaMP). The simulation results show that proposed approach can achieve a higher quality than other exiting compressive video coding schemes.
Keywords :
"Matching pursuit algorithms","Video coding","Image reconstruction","Sensors","Image coding"
Conference_Titel :
Machine Vision and Image Processing (MVIP), 2015 9th Iranian Conference on
Electronic_ISBN :
2166-6784
DOI :
10.1109/IranianMVIP.2015.7397528