• DocumentCode
    3524140
  • Title

    Sparse decomposition of two dimensional signals

  • Author

    Ghaffari, Aboozar ; Babaie-Zadeh, Massoud ; Jutten, Christian

  • Author_Institution
    Electr. Eng. Dept., Sharif Univ. of Technol., Tehran
  • fYear
    2009
  • fDate
    19-24 April 2009
  • Firstpage
    3157
  • Lastpage
    3160
  • Abstract
    In this paper, we consider sparse decomposition (SD) of two-dimensional (2D) signals on overcomplete dictionaries with separable atoms. Although, this problem can be solved by converting it to the SD of one-dimensional (1D) signals, this approach requires a tremendous amount of memory and computational cost. Moreover, the uniqueness constraint obtained by this approach is too restricted. Then in the paper, we present an algorithm to be used directly for sparse decomposition of 2D signals on dictionaries with separable atoms. Moreover, we will state another uniqueness constraint for this class of decomposition. Our algorithm is obtained by modifying the Smoothed L0 (SL0) algorithm, and hence we call it two-dimensional SL0 (2D-SL0).
  • Keywords
    image coding; sparse matrices; compressive sensing; image coding; sparse coding; sparse decomposition; sparse representation; Computational efficiency; Dictionaries; Discrete Fourier transforms; Image coding; Matching pursuit algorithms; Matrix decomposition; Signal processing algorithms; Signal resolution; Sparks; Vectors; Compressive Sensing; Image Coding; Sparse Coding; Sparse Decomposition; Sparse Representation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
  • Conference_Location
    Taipei
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4244-2353-8
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2009.4960294
  • Filename
    4960294