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Design of signal-adapted multidimensional lifting scheme for lossy coding
Annabelle Gouze1, Marc Antonini, Michel Barlaud
1Université catholique de Louvain, 1348 Louvain, Belgium.
Summary
This study introduces a novel lifting filter design for multidimensional nonseparable wavelet transforms, enhancing image compression efficiency. The method optimizes filters for signal statistics, reducing costs and improving performance on JPEG2000 and satellite data.
Area of Science:
- Digital Signal Processing
- Image Compression
- Wavelet Transforms
Background:
- Multidimensional nonseparable wavelet transforms are crucial for image processing.
- Designing efficient lifting filters, especially for quincunx sampling, presents significant challenges.
- Existing methods often address specific cases, limiting general applicability.
Purpose of the Study:
- To propose a generalized method for designing lifting filters for multidimensional nonseparable wavelet transforms.
- To develop less expensive, signal-adapted filters for enhanced compression efficiency.
- To integrate lifting theory with Wiener's optimization for improved filter design.
Main Methods:
- A two-step lifting scheme combining lifting theory with Wiener's optimization.
- Designing the prediction step to minimize signal variance.
- Designing the update step to minimize reconstruction error.
Main Results:
- The proposed method is demonstrated for 2-D separable and quincunx image cases.
- Results are validated using the JPEG2000 database and satellite imagery.
- The approach enables the design of cost-effective filters tailored to signal statistics.
Conclusions:
- The novel lifting filter design method offers enhanced compression efficiency.
- The approach provides a more general solution for quincunx filter design.
- The method shows promising performance for lossy image compression applications.
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