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Extended lapped transform in image coding.

R L de Queiroz1, K R Rao

  • 1Dept. of Electr. Eng., Texas Univ., Arlington, TX.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1995
PubMed
Summary
This summary is machine-generated.

The Extended Lapped Transform (ELT) shows promise for image coding, outperforming the Discrete Cosine Transform (DCT) and Lapped Orthogonal Transform (LOT) in quality and artifact reduction.

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Area of Science:

  • Image processing and computer vision
  • Signal processing and data compression

Background:

  • The Discrete Cosine Transform (DCT) is widely used in image compression standards.
  • Limitations of DCT include blocking artifacts and susceptibility to transmission errors.
  • Lapped transforms offer improved performance but require efficient implementation.

Purpose of the Study:

  • To investigate the Extended Lapped Transform (ELT) as a potential replacement for DCT in image coding.
  • To evaluate ELT's performance based on image quality, artifact reduction, error robustness, and scalability.
  • To develop a fast implementation algorithm for ELT.

Main Methods:

  • Comparative analysis of ELT against DCT and Lapped Orthogonal Transform (LOT).
  • Evaluation metrics included objective and subjective reconstructed image quality.
  • Assessment of blocking artifact reduction, transmission error robustness, and filtering for scalability.
  • Development of a fast implementation algorithm for ELT with overlap factor 2 (ELT-2) using symmetric extensions.

Main Results:

  • ELT-2 demonstrated superior performance compared to both DCT and LOT.
  • Enhanced reconstructed image quality (objective and subjective) was observed.
  • Significant reduction in blocking artifacts was achieved.
  • Improved robustness against transmission errors and effective filtering for scalability were noted.

Conclusions:

  • The Extended Lapped Transform (ELT), particularly ELT-2, is a viable and superior alternative to DCT for specific image coding applications.
  • ELT offers enhanced image quality, reduced artifacts, and better robustness, making it suitable for advanced image compression.
  • The developed fast implementation algorithm facilitates practical application of ELT-2.