Multi-frame compression: theory and design

被引:197
|
作者
Engan, K [1 ]
Aase, SO [1 ]
Husoy, JH [1 ]
机构
[1] Hogskolen & Stavanger, Dept Elect & Comp Engn, N-4091 Stavanger, Norway
关键词
signal compression; frames; overcomplete dictionaries; codebook design; frame design; method of optimal directions (MOD); matching pursuit; vector selection (basis selection) algorithms; multi-frame compression (MFC) scheme;
D O I
10.1016/S0165-1684(00)00072-4
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper consist of two parts. The first part concerns approximation capabilities in using an overcomplete dictionary, a frame, for block coding. A frame design technique for use with vector selection algorithms, for example matching pursuits (MP), is presented. We call the technique method of optimal directions (MOD). It is iterative and requires a training set of signal vectors. Experiments demonstrate that the approximation capabilities of the optimized frames are significantly better than those obtained using frames designed by ad hoc techniques or chosen in an ad hoc fashion. Experiments show typical reduction in mean squared error (MSE) by 30-80% for speech and electrocardiogram (ECG) signals. The second part concerns a complete compression scheme using a set of optimized frames, and evaluates both the use of fixed size and variable size frames. A signal compression scheme using frames optimized with the MOD technique is proposed. The technique, called multi-frame compression (MFC) uses several different frames, each optimized for a fixed number of selected frame vectors in each approximation. We apply the MOD and the MFC scheme to ECG signals. The coding results are compared with results obtained when using transform-based compression schemes like the discrete cosine transform (DCT) in combination with run-length and entropy coding. The experiments demonstrate improved rate-distortion performance by 2-4 dB for the MFC scheme when compared to the DCT at low bit-rates. They also show that variable sized frames in the compression scheme perform better than fixed sized frames. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:2121 / 2140
页数:20
相关论文
共 50 条
  • [31] Multi-frame image restoration for face recognition
    Wheeler, Frederick W.
    Liu, Xiaoming
    Tu, Peter H.
    Hoctor, Ralph T.
    2007 IEEE WORKSHOP ON SIGNAL PROCESSING APPLICATIONS FOR PUBLIC SECURITY AND FORENSICS, 2007, : 6 - +
  • [32] Handheld Multi-Frame Super-Resolution
    Wronski, Bartlomiej
    Garcia-Dorado, Ignacio
    Ernst, Manfred
    Kelly, Damien
    Krainin, Michael
    Liang, Chia-Kai
    Levoy, Marc
    Milanfar, Peyman
    ACM TRANSACTIONS ON GRAPHICS, 2019, 38 (04):
  • [33] Multi-Frame Super Resolution for Ocular Biometrics
    Reddy, Narsi
    Noor, Dewan Fahim
    Li, Zhu
    Derakhshani, Reza
    PROCEEDINGS 2018 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), 2018, : 566 - 574
  • [34] Interactive multi-frame reconstruction for mobile devices
    Lopez, Miguel Bordallo
    Hannuksela, Jari
    Silven, Olli
    Vehvilainen, Markku
    MULTIMEDIA TOOLS AND APPLICATIONS, 2014, 69 (01) : 31 - 51
  • [35] Multi-frame visualization for detonation wave diffraction
    Y. Nagura
    J. Kasahara
    A. Matsuo
    Shock Waves, 2016, 26 : 645 - 656
  • [36] Optimal multi-frame correspondence with assignment tensors
    Oliveira, R.
    Ferreira, R.
    Costeira, J. P.
    COMPUTER VISION - ECCV 2006, PT 3, PROCEEDINGS, 2006, 3953 : 490 - 501
  • [37] Multi-frame simultaneous motion estimation and segmentation
    Feghali, R
    IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2005, 51 (01) : 245 - 248
  • [38] Multi-Frame Super-Resolution: A Survey
    Khattab, Mahmoud M.
    Zeki, Akram M.
    Alwan, Ali A.
    Badawy, Ahmed S.
    Thota, Lalitha Saroja
    2018 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (IEEE ICCIC 2018), 2018, : 348 - 355
  • [39] Video Deflickering Using Multi-Frame Optimization
    Li, Chao
    Chen, Zhihua
    Sheng, Bin
    Li, Ping
    He, Gaoqi
    2018 IEEE FOURTH INTERNATIONAL CONFERENCE ON MULTIMEDIA BIG DATA (BIGMM), 2018,
  • [40] Visual Odometry by Multi-frame Feature Integration
    Badino, Hernan
    Yamamoto, Akihiro
    Kanade, Takeo
    2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW), 2013, : 222 - 229