• DocumentCode
    1093402
  • Title

    Space-frequency localized image compression

  • Author

    Wong, Ping Wah ; Noyes, Steven

  • Author_Institution
    Hewlett-Packard Co., Palo Alto, CA, USA
  • Volume
    3
  • Issue
    3
  • fYear
    1994
  • fDate
    5/1/1994 12:00:00 AM
  • Firstpage
    302
  • Lastpage
    307
  • Abstract
    Subband and wavelet-based image compression can be viewed as frequency oriented techniques because each subimage in the decomposition is essentially a band-pass version of the original image. The authors suggest a space-frequency partition scheme to fully exploit the excellent localization properties of wavelets in both the spatial and frequency domains. Due to the relatively large number of blocks in this partition compared with traditional subband coders, the rate required for communicating the quantizer configurations must be taken into account. An iterative bit allocation algorithm is suggested that minimizes the mean square error given the overall rate for specifying the quantization configuration and for quantizing the wavelet coefficients. Images encoded using scalar quantization under this scheme show improvements in PSNR versus rate over traditional subband and wavelet-based methods
  • Keywords
    data compression; frequency-domain analysis; image coding; iterative methods; wavelet transforms; frequency domains; frequency oriented techniques; iterative bit allocation algorithm; localization properties; mean square error; quantizer configurations; scalar quantization; space-frequency localized image compression; space-frequency partition scheme; spatial domain; subimage; wavelet coefficients; Bit rate; Frequency domain analysis; Image coding; Iterative algorithms; Mean square error methods; PSNR; Partitioning algorithms; Quantization; Wavelet coefficients; Wavelet domain;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1057-7149
  • Type

    jour

  • DOI
    10.1109/83.287024
  • Filename
    287024