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Improved MPEG-4 still texture image coding under noisy environment.

Tommy C L Chan1, Tai-Chiu Hsung, Daniel Pak-Kong Lun

  • 1Dept. of Electron. and Inf. Eng., Hong Kong Polytech. Univ., China. tommy@eie.polyu.edu.hk

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 2, 2008
PubMed
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Compressing noisy images with the MPEG-4 still texture codec can yield an optimal peak-signal-to-noise ratio (PSNR) but introduces artifacts. A novel adaptive thresholding technique improves visual quality and PSNR for noisy image compression.

Area of Science:

  • Digital Image Processing
  • Video Compression Standards
  • Signal Processing

Background:

  • MPEG-4 still texture image codec performance with noisy images is not well understood.
  • Compression artifacts, particularly the
  • cross
  • shape, degrade visual quality in noisy image compression.
  • Existing methods may not effectively balance compression rate and image fidelity for noisy content.

Purpose of the Study:

  • Analyze the causes of optimal operating points and
  • cross
  • artifacts in MPEG-4 compression of noisy images.
  • Propose an adaptive thresholding technique to mitigate these artifacts.
  • Evaluate the effectiveness of the proposed technique in improving visual quality and peak-signal-to-noise ratio (PSNR).

Related Experiment Videos

Main Methods:

  • Analysis of MPEG-4 still texture image codec behavior with noisy input data.
  • Development of an adaptive thresholding algorithm integrated into the MPEG-4 quantization process.
  • Analytical study for threshold value selection and validation.
  • Comparative evaluation of the proposed method against the traditional MPEG-4 codec.

Main Results:

  • Identified an optimal operating point for peak-signal-to-noise ratio (PSNR) in low bit rate regions for noisy images.
  • Characterized the
  • cross
  • shape artifact as a significant visual degradation issue.
  • Demonstrated substantial improvements in visual quality and PSNR using the proposed adaptive thresholding technique.
  • Confirmed that the decoder remains unchanged, simplifying implementation.

Conclusions:

  • The proposed adaptive thresholding technique effectively removes
  • cross
  • artifacts and enhances image quality for noisy images compressed with MPEG-4.
  • The method offers a practical solution with minimal modification to the encoder.
  • This approach significantly improves upon the performance of the traditional MPEG-4 still texture image codec for noisy image coding.