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Related Experiment Videos

Nonexpansive pyramid for image coding using a nonlinear filterbank.

R L de Queiroz1, D A Florêncio, R W Schafer

  • 1Xerox Corporation, Webster, NY 14580, USA. queiroz@wrc.xerox.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 13, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a new, efficient image coding method using nonexpansive pyramidal decomposition. This technique reduces computational complexity and improves image quality, offering lossless coding capabilities.

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Area of Science:

  • Digital image processing
  • Signal processing
  • Image compression

Background:

  • Traditional image coding methods like JPEG using Discrete Cosine Transform (DCT) face limitations in computational complexity and artifact generation.
  • Pyramidal decomposition offers a hierarchical approach to image representation, but nonexpansive methods with high coding efficiency are sought.

Purpose of the Study:

  • To propose and evaluate a novel nonexpansive pyramidal decomposition for low-complexity image coding.
  • To integrate this decomposition into a Joint Photographic Expert Group (JPEG) compatible coder, replacing the DCT.
  • To demonstrate the advantages of the proposed method over existing DCT-based JPEG coders.

Main Methods:

  • A nonlinear filterbank is employed for image decomposition into low- and high-pass signals.
  • The filterbank is recursively applied to the low-pass signal, creating a pyramid structure.
  • Transformed samples are blocked and utilized within a JPEG framework, substituting the DCT.

Main Results:

  • The proposed method achieves perfect reconstruction due to its inherent structure.
  • Nonlinear filters are selected for enhanced performance.
  • The new coder significantly reduces computation compared to DCT-based JPEG.
  • Improved encoding of image edges and elimination of blocking artifacts are observed.
  • The method supports lossless coding.

Conclusions:

  • The proposed nonexpansive pyramidal decomposition offers a computationally efficient and high-performance alternative for image coding.
  • It effectively addresses limitations of DCT-based methods, providing superior edge representation and artifact reduction.
  • This approach enables high-quality, lossless image compression with reduced complexity.