TY - GEN
T1 - A low-complexity video coding scheme based on compressive sensing
AU - Hou, Yantian
AU - Liu, Feng
PY - 2011
Y1 - 2011
N2 - Traditional video coding method is able to achieve wonderful performance in data compressing. However, it has high complexity, which is not suitable for some environments where low complexity coding is needed. A new method of video coding which is based on compressive sensing is proposed. In this system, the sparsity of residual of successive frames is exploited, which is a crucial requirement in CS theory. This method encodes video frames in a fast and low-complexity way, while the compressive rate of data remains low. The reconstruction of original video frame, as well as the PSNR-rate curve under this framework, is given.
AB - Traditional video coding method is able to achieve wonderful performance in data compressing. However, it has high complexity, which is not suitable for some environments where low complexity coding is needed. A new method of video coding which is based on compressive sensing is proposed. In this system, the sparsity of residual of successive frames is exploited, which is a crucial requirement in CS theory. This method encodes video frames in a fast and low-complexity way, while the compressive rate of data remains low. The reconstruction of original video frame, as well as the PSNR-rate curve under this framework, is given.
KW - compressive sensing
KW - sparsity
KW - video coding
UR - https://www.scopus.com/pages/publications/83455259948
U2 - 10.1109/ISCID.2011.184
DO - 10.1109/ISCID.2011.184
M3 - 会议稿件
AN - SCOPUS:83455259948
SN - 9780769545004
T3 - Proceedings - 2011 4th International Symposium on Computational Intelligence and Design, ISCID 2011
SP - 326
EP - 329
BT - Proceedings - 2011 4th International Symposium on Computational Intelligence and Design, ISCID 2011
T2 - 2011 4th International Symposium on Computational Intelligence and Design, ISCID 2011
Y2 - 28 October 2011 through 30 October 2011
ER -