A novel video codec scheme based on compressive sensing

被引:0
|
作者
Dong, Guanghui [1 ,2 ]
Xi, Zhihong [1 ]
机构
[1] College of Information and Communications Engineering, Harbin Engineering University
[2] College of Mechanical and Electronic Engineering, Northeast Forestry University
来源
Journal of Information and Computational Science | 2013年 / 10卷 / 14期
关键词
Compressive sensing; Measurement; Reconstruction; Sparse representation; Video codec;
D O I
10.12733/jics20102754
中图分类号
学科分类号
摘要
In order to solve the problem of traditional video codec high sampling rate, a novel video codec scheme is proposed based on compressive sensing. At the encoding process, the frames in video sequence are divided into groups, in each group include intra and inter frames, random measurement matrix is constructed to measure different frames. Then the measurement values are quantized, the quantization codes are transmitted. At decoding process, each frame is reconstructed using the StOMP algorithm. Experimental results show that the proposed method is superiority over the tradition video codec with keeping the same quality of the video, and it can reduce quantization number significantly, realize easily. The codec scheme is more efficiently for non-rapid moving video sequence, the PSNR is above 45 dB. 1548-7741/Copyright © 2013 Binary Information Press.
引用
收藏
页码:4681 / 4689
页数:8
相关论文
共 50 条
  • [41] Hierarchical frame based spatial-temporal recovery for video compressive sensing coding
    Gao, Xinwei
    Jiang, Feng
    Liu, Shaohui
    Che, Wenbin
    Fan, Xiaopeng
    Zhao, Debin
    NEUROCOMPUTING, 2016, 174 : 404 - 412
  • [42] Adaptive embedding: A novel meaningful image encryption scheme based on parallel compressive sensing and slant transform
    Jiang, Donghua
    Liu, Lidong
    Zhu, Liya
    Wang, Xingyuan
    Rong, Xianwei
    Chai, Hongxiang
    SIGNAL PROCESSING, 2021, 188
  • [43] Compressive video sensing with side information
    Yuan, Xin
    Sun, Yangyang
    Pang, Shuo
    APPLIED OPTICS, 2017, 56 (10) : 2697 - 2704
  • [44] Deep Sensing for Compressive Video Acquisition
    Yoshida, Michitaka
    Torii, Akihiko
    Okutomi, Masatoshi
    Taniguchi, Rin-ichiro
    Nagahara, Hajime
    Yagi, Yasushi
    SENSORS, 2023, 23 (17)
  • [45] Compressive video sensing with limited measurements
    Li, Tao
    Wang, Xiaohua
    Wang, Weihe
    Katsaggelos, Aggelos K.
    JOURNAL OF ELECTRONIC IMAGING, 2013, 22 (04)
  • [46] Video Compressive Sensing with Redundant Dictionary
    Li, Tao
    Wang, Xiaohua
    FIFTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2013), 2013, 8878
  • [47] Iterative Reweighted Tikhonov-Regularized Multihypothesis Prediction Scheme for Distributed Compressive Video Sensing
    Chen, Can
    Zhou, Chao
    Liu, Pengyuan
    Zhang, Dengyin
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2020, 30 (01) : 1 - 10
  • [48] Adaptive image compression based on compressive sensing for video sensor nodes
    Xufan Zhang
    Yong Wang
    Dianhong Wang
    Yamin Li
    Multimedia Tools and Applications, 2018, 77 : 13679 - 13699
  • [49] Dynamic measurement rate allocation for distributed compressive video sensing
    Chen, Hung-Wei
    Kang, Li-Wei
    Lu, Chun-Shien
    VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2010, 2010, 7744
  • [50] Graph-spectral hyperspectral video restoration based on compressive sensing
    Tan Cui-mei
    Xu Ting-fa
    Ma Xu
    Zhang Yu-han
    Wang Xi
    Yan Ge
    CHINESE OPTICS, 2018, 11 (06): : 949 - 957