TY - GEN
T1 - Improved Distributed Compressive Sensing Basing on HEVC ME and BM3D-AMP Algorithm
AU - Li, Zejin
AU - Wu, Shaohua
AU - Jiao, Jian
AU - Zhang, Qinyu
N1 - Publisher Copyright:
© 2020, Springer Nature Singapore Pte Ltd.
PY - 2020
Y1 - 2020
N2 - The distributed compressive video sensing (DCVS) system greatly reduces the pressure on the encoder by transferring the computational complexity to the decoder, which is suitable for the limited-resource video sensing and transmission environment, in the meantime, get the better performance from key (K) frames and non-key (CS) frames. In this paper, we use the approximate message passing (AMP) algorithm reconstruct the K-frames. In order to improve the quality of the reconstructed K-frames, we add the block-matching 3D filtering (BM3D) denoising strategy based on the AMP algorithm. For the CS-frames, we improve the reconstructed CS-frames by improving the accuracy of side information (SI) frames by proposing a new high efficiency video coding (HEVC) motion estimation (ME) algorithm with motion vector (MV) prediction method. After we obtain the SI frames and combine the compressed value of the CS-frames with the side information (SI) fusion algorithm based on the difference compensation algorithm, the high accuracy SI frame is integrated into the reconstruction algorithm of the CS-frames. The experimental results demonstrate that our algorithms achieve higher subjective visual quality and peak signal-to-noise ratio than the traditional methods.
AB - The distributed compressive video sensing (DCVS) system greatly reduces the pressure on the encoder by transferring the computational complexity to the decoder, which is suitable for the limited-resource video sensing and transmission environment, in the meantime, get the better performance from key (K) frames and non-key (CS) frames. In this paper, we use the approximate message passing (AMP) algorithm reconstruct the K-frames. In order to improve the quality of the reconstructed K-frames, we add the block-matching 3D filtering (BM3D) denoising strategy based on the AMP algorithm. For the CS-frames, we improve the reconstructed CS-frames by improving the accuracy of side information (SI) frames by proposing a new high efficiency video coding (HEVC) motion estimation (ME) algorithm with motion vector (MV) prediction method. After we obtain the SI frames and combine the compressed value of the CS-frames with the side information (SI) fusion algorithm based on the difference compensation algorithm, the high accuracy SI frame is integrated into the reconstruction algorithm of the CS-frames. The experimental results demonstrate that our algorithms achieve higher subjective visual quality and peak signal-to-noise ratio than the traditional methods.
KW - Approximate message passing
KW - Block-matching 3D filtering
KW - Distributed compressive video sensing
KW - High efficiency video coding
UR - https://www.scopus.com/pages/publications/85071478095
U2 - 10.1007/978-981-13-6504-1_58
DO - 10.1007/978-981-13-6504-1_58
M3 - 会议稿件
AN - SCOPUS:85071478095
SN - 9789811365034
T3 - Lecture Notes in Electrical Engineering
SP - 475
EP - 482
BT - Communications, Signal Processing, and Systems - Proceedings of the 2018 CSPS Volume II
A2 - Liang, Qilian
A2 - Liu, Xin
A2 - Na, Zhenyu
A2 - Wang, Wei
A2 - Mu, Jiasong
A2 - Zhang, Baoju
PB - Springer Verlag
T2 - International Conference on Communications, Signal Processing, and Systems, CSPS 2018
Y2 - 14 July 2018 through 16 July 2018
ER -