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Synthesis filter bank optimization in two-dimensional separable subband coding systems.

G Calvagno1, G A Mian, R Rinaldo

  • 1Dipartimento di Elettronica e Informatica, 35131 Padova, Italy.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 12, 2008
PubMed
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Designing optimal synthesis filters for subband coding minimizes reconstruction error, especially with dithered quantization. This research extends 1-D methods to 2-D separable systems for improved image and video transmission.

Area of Science:

  • Digital Signal Processing
  • Image and Video Compression
  • Filter Bank Design

Background:

  • Subband coding is vital for visual communications.
  • Perfect reconstruction is suboptimal with quantization errors.
  • Designing optimal filters for 2-D separable subband systems is challenging.

Purpose of the Study:

  • To design synthesis filters minimizing mean squared error in 2-D separable subband coding.
  • To address the nonlinear optimization problem for filter design.
  • To extend existing 1-D optimal filter design procedures to 2-D.

Main Methods:

  • Proposed a suboptimal solution for 2-D separable synthesis filter design.
  • Extended a 1-D optimal filter design procedure.
  • Modeled input images as a 2-D separable Markov process with additive white noise.

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Main Results:

  • The designed filters offer significant gains over perfect reconstruction solutions.
  • The proposed technique is particularly effective with dithered quantization.
  • The image model proved useful for synthesis filter design.

Conclusions:

  • The developed suboptimal filter design enhances 2-D separable subband coding performance.
  • The proposed method effectively handles quantization effects in image and video transmission.
  • The image modeling approach simplifies and improves filter design.