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Wiener filter-based error resilient time-domain lapped transform.

Jie Liang1, Chengjie Tu, Lu Gan

  • 1School of Engineering Science, Simon Fraser University, Burnaby, BC V5A 1S6 Canada. jiel@sfu.ca

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 3, 2007
PubMed
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This study introduces an improved error-resilient time-domain lapped transform (TDLT) design. The new Wiener filter-based method enhances image coding performance by minimizing mean-squared error.

Area of Science:

  • Signal Processing
  • Image Compression
  • Transform Coding

Background:

  • Time-domain lapped transforms (TDLTs) are crucial for efficient image compression.
  • Existing methods for error resilience in TDLTs have limitations.
  • Mean reconstruction and linear interpolation are common techniques with specific constraints.

Purpose of the Study:

  • To formulate the design of error-resilient TDLTs as a linear minimal mean-squared error problem.
  • To develop optimal Wiener solutions and practical simplifications for TDLT design.
  • To improve upon existing methods for image coding with enhanced error resilience.

Main Methods:

  • Formulation as a linear minimal mean-squared error problem.
  • Development of optimal Wiener filters and simplified versions.

Related Experiment Videos

  • Analysis of the persymmetric structure of Wiener filters.
  • Scrutiny and improvement of existing design criteria.

    • Main Results:

    • The optimal Wiener solution for error-resilient TDLT design is derived.
    • Simplified solutions offering a balance between complexity and performance are presented.
    • The persymmetric structure of the Wiener filters is mathematically proven.
    • Existing mean reconstruction and linear interpolation methods are shown to be special cases of the proposed framework.

    Conclusions:

    • The proposed Wiener filter-based framework offers improved performance for error-resilient TDLT design.
    • The method provides a unified approach encompassing existing techniques.
    • Experimental results demonstrate the effectiveness of the proposed method in image coding applications.