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Related Concept Videos

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Convergence of Fourier Series

The Fourier series is a powerful mathematical tool for representing periodic signals as an infinite sum of complex exponentials. In practice, this infinite series is truncated to a finite number of terms, yielding a partial sum. This truncation makes the approximation of the signal feasible but introduces certain challenges, particularly near discontinuities, known as the Gibbs phenomenon.
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Related Experiment Video

Updated: Jul 7, 2026

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
11:00

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

Wavelet filter evaluation for image compression.

J D Villasenor1, B Belzer, J Liao

  • 1Dept. of Electr. Eng., California Univ., Los Angeles, CA.

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

Selecting the right wavelet filter bank is crucial for image compression quality and system design. This study introduces new metrics beyond regularity for reliable filter evaluation, identifying optimal filters for image coding.

Related Experiment Videos

Last Updated: Jul 7, 2026

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section
11:00

Experimental Investigation of Secondary Flow Structures Downstream of a Model Type IV Stent Failure in a 180° Curved Artery Test Section

Published on: July 19, 2016

Area of Science:

  • Digital Signal Processing
  • Image Compression
  • Wavelet Theory

Background:

  • Filter bank selection critically impacts wavelet compression performance and system design.
  • Regularity is an insufficient metric for predicting compression efficiency.
  • Existing evaluation methods lack relevance for image coding applications.

Purpose of the Study:

  • To develop reliable filter evaluation metrics for wavelet-based image compression.
  • To identify optimal biorthogonal wavelet filter banks for image coding.
  • To explore novel filter properties beneficial for system design.

Main Methods:

  • Characterizing filter banks as linear shift-variant systems.
  • Utilizing impulse response and step response alongside regularity for evaluation.
  • Systematic evaluation of minimum-order biorthogonal wavelet filter banks (synthesis/analysis pairs < 36 taps).

Main Results:

  • Developed novel, reliable filter evaluation metrics relevant to image coding.
  • Evaluated over 4300 candidate filter banks.
  • Identified and presented superior filter banks for image compression, including new candidates.

Conclusions:

  • Impulse and step response provide superior filter evaluation for image compression compared to regularity alone.
  • The identified filters offer enhanced performance and attractive properties for image compression system design.
  • This systematic approach facilitates the discovery of optimal wavelet filters for digital imaging.