• DocumentCode
    1123259
  • Title

    Restructured recursive DCT and DST algorithms

  • Author

    Lee, Peizong ; Huang, Fang-Yu

  • Author_Institution
    Inst. of Inf. Sci., Acad. Sinica, Taipei, Taiwan
  • Volume
    42
  • Issue
    7
  • fYear
    1994
  • fDate
    7/1/1994 12:00:00 AM
  • Firstpage
    1600
  • Lastpage
    1609
  • Abstract
    The discrete cosine transform (DCT) and the discrete sine transform (DST) have found wide applications in speech and image processing, as well as telecommunication signal processing for the purpose of data compression, feature extraction, image reconstruction, and filtering. In this paper, we present new recursive algorithms for the DCT and the DST. The proposed method is based on certain recursive properties of the DCT coefficient matrix, and can be generalized to design recursive algorithms for the 2-D DCT and the 2-D DST. These new structured recursive algorithms are able to decompose the DCT and the DST into two balanced lower-order subproblems in comparison to previous research works. Therefore, when converting our algorithms into hardware implementations, we require fewer hardware components than other recursive algorithms. Finally, we propose two parallel algorithms for accelerating the computation
  • Keywords
    discrete cosine transforms; filtering and prediction theory; matrix algebra; parallel algorithms; signal processing; speech analysis and processing; 2-D DCT; 2-D DST; DCT coefficient matrix; data compression; discrete cosine transform; discrete sine transform; feature extraction; filtering; image processing; image reconstruction; parallel algorithms; recursive properties; restructured recursive DCT algorithm; restructured recursive DST algorithms; speech processing; telecommunication signal processing; Data compression; Discrete cosine transforms; Discrete transforms; Feature extraction; Filtering; Hardware; Image processing; Image reconstruction; Signal processing algorithms; Speech processing;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/78.298269
  • Filename
    298269