• DocumentCode
    934623
  • Title

    Multilevel block truncation coding using a minimax error criterion for high-fidelity compression of digital images

  • Author

    Wu, Yiyan ; Coll, David C.

  • Volume
    41
  • Issue
    8
  • fYear
    1993
  • fDate
    8/1/1993 12:00:00 AM
  • Firstpage
    1179
  • Lastpage
    1191
  • Abstract
    An encoding technique called multilevel block truncation coding that preserves the spatial details in digital images while achieving a reasonable compression ratio is described. An adaptive quantizer-level allocation scheme which minimizes the maximum quantization error in each block and substantially reduces the computational complexity in the allocation of optimal quantization levels is introduced. A 3.2:1 compression can be achieved by the multilevel block truncation coding itself. The truncated, or requantized, data are further compressed in a second pass using combined predictive coding, entropy coding, and vector quantization. The second pass compression can be lossless or lossy. The total compression ratios are about 4.1:1 for lossless second-pass compression, and 6.2:1 for lossy second-pass compression. The subjective results of the coding algorithm are quite satisfactory, with no perceived visual degradation
  • Keywords
    block codes; data compression; filtering and prediction theory; image coding; minimax techniques; vector quantisation; adaptive quantizer-level allocation scheme; computational complexity; digital images; encoding technique; entropy coding; high-fidelity compression; image coding; lossless compression; lossy compression; minimax error criterion; multilevel block truncation coding; optimal quantization levels; predictive coding; second pass compression; vector quantization; Computational complexity; Digital images; Entropy coding; Image coding; Image reconstruction; Low pass filters; Minimax techniques; Pixel; Predictive coding; Vector quantization;
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/26.231961
  • Filename
    231961