Title :
Motion Estimation in Measurement Domain for Compressed Video Sensing
Author :
Jie Guo ; Bin Song ; Haixiao Liu ; Hao Qin
Author_Institution :
State Key Lab. of Integrated Services Networks, Xidian Univ., Xi´an, China
Abstract :
Compressed sensing (CS) is a new approach to signal acquisition that can potentially allow us to design very simple video encoders, which then develops as the compressed video sensing (CVS). However, a unique characteristic of CS is that it directly captures the signal in the measurement domain, which then makes these traditional techniques which are used to remove the time redundancy of video signals, as motion estimation, not suitable for compressively sampled videos. In this paper, by analyzing the inner spatial relation in original signals and relationship between original signals and measurements, a new motion estimation method in measurement domain for CVS is proposed. By using this method, we can perform motion estimation directly with the sampled measurements, thus offering convenience to remove the time redundancy of videos directly in measurement domain.
Keywords :
compressed sensing; image sampling; motion estimation; redundancy; signal detection; video coding; CS; CVS; compressed video sensing; measurement domain; motion estimation; signal acquisition; video encoder; video sampling; video signal time redundancy removal; Correlation; Current measurement; Image reconstruction; Motion estimation; Motion measurement; Sensors; Vectors; compressed sensing; measurements; motion estimation; video signal;
Conference_Titel :
Computer and Information Technology (CIT), 2014 IEEE International Conference on
Conference_Location :
Xi´an
DOI :
10.1109/CIT.2014.76