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Subband-coded image reconstruction for lossy packet networks.

S S Hemami1, R M Gray

  • 1Sch. of Electr. Eng., Cornell Univ., Ithaca, NY.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
PubMed
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This study introduces novel methods for reconstructing lost digital image data in subband coding over packet networks. These techniques improve visual quality by intelligently interpolating missing low- and high-frequency coefficients.

Area of Science:

  • Digital image processing
  • Signal processing
  • Computer networks

Background:

  • Digital subband-coded images transmitted over lossy networks face reconstruction challenges at the decoder.
  • Loss of subband coefficients degrades image quality and requires robust recovery methods.

Purpose of the Study:

  • To present two novel techniques for reconstructing lost subband coefficients in digital images.
  • To enhance visual quality and ensure accurate edge placement during image reconstruction.

Main Methods:

  • Low-frequency coefficient reconstruction using a cubic interpolative surface adapted to detected edges.
  • High-frequency coefficient reconstruction via linear interpolation.
  • Edge detection by analyzing high-frequency bands without processing low-frequency bands.

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Main Results:

  • The low-frequency algorithm maintains smoothness and exploits intraband correlation for accurate interpolation.
  • Edge placement is improved by adapting the interpolation grid based on identified edges.
  • High-frequency reconstruction using linear interpolation complements edge placement and offers good visual performance.

Conclusions:

  • The developed algorithm effectively reconstructs lost coefficients (single, vector, or block) in subband-coded images.
  • The techniques are applicable to various source coding methods for improved transmission over lossy networks.
  • The method ensures high visual quality and accurate edge representation in reconstructed images.