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Image coding with uniform and piecewise-uniform vector quantizers.

D G Jeong1, J D Gibson

  • 1Dept. of Avionics Eng., Hankuk Aviation Univ., Kyunggi.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1995
PubMed
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New lattice vector quantizer methods offer excellent performance for nonuniform sources. These techniques enable fast, efficient image compression using discrete cosine transform coefficients.

Area of Science:

  • Signal Processing
  • Image Compression
  • Data Quantization

Background:

  • Efficient data compression is crucial for digital media.
  • Lattice vector quantization (LVS) offers a structured approach to quantization.
  • Nonuniform data sources present challenges for traditional quantization methods.

Purpose of the Study:

  • To develop novel lattice vector quantizer design procedures for nonuniform sources.
  • To introduce analytical methods for lattice truncation, scaling, and multidimensional companding.
  • To evaluate the performance of these new quantizers in image compression applications.

Main Methods:

  • Development of analytical procedures for lattice vector quantizer design.
  • Application of piecewise-linear multidimensional companding techniques.

Related Experiment Videos

  • Quantization of discrete cosine transform (DCT) coefficients using uniform and piecewise-uniform lattice vector quantizers.

    • Main Results:

    • Achieved excellent performance with lattice vector quantizers for nonuniform sources.
    • Maintained structural properties necessary for fast quantization.
    • Demonstrated competitive or superior objective and subjective performance compared to existing methods.

    Conclusions:

    • The proposed lattice vector quantizer design procedures are effective for nonuniform sources.
    • These methods provide a balance between performance and computational complexity.
    • The approach shows significant potential for image compression and other data quantization tasks.