Fixed Analysis Adaptive Synthesis
Filter Banks
By
Clyde A. Lettsome, P.E.
Mark J. T. Smith, Ph.D.
Russell M. Mersereau, Ph...
2 Outline
 Introduction
 Time-Varying FIR Filter Banks
 Designing The Filters
 Results And Conclusions
 Future Work
3
Introduction
 Analysis-synthesis filter banks have been employed
pervasively in the signal processing community for
mor...
4
Introduction
When bit rates are lowered, inevitably distortions occur
Challenge: designing of subband image compressio...
5
Time-varying Filter Banks
Prior Solution- Time-varying filter banks evolution
 Nayebi explored a technique where analys...
6
Time-varying Filter Banks
A disadvantage is that the synthesis filters must be
changed in lock step with the analysis fi...
7
Time-varying Filter Banks
Analysis
Single Set
Analysis
Multiple Set
Synthesis
Single Set
Numerous
Researchers
Convention...
8
Time-varying Filter Banks
 Our Solution- Adaptive FIR filter banks
for image coding:
 have the analysis filters fixed,...
9
Time-varying Filter Banks
10
Designing the Filters
11
Designing the Filters
•Nayebi introduced a time domain formulation that
allowed even length FIR filters to be design at...
12
Designing the Filters
An optimization equation is formed using:
• reconstruction error component
•component associated ...
13
Designing the Filters
where
14
Result and Conclusion
Conventional SPIHT Coder
Bit Rate: 0.5 bpp
PSNR: 31.47 dB
Adaptive SPIHT Coder
Method applied: La...
15
Future Work
 Applying technique on more levels
 Develop a more sophisticated phase selection
approach
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2008 Spie Defense + Security Presentation

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Fixed Analysis Adaptive Synthesis Filter Banks for Image Compression. This presentation was given at the 2008 SPIE Defense + Security Conference in Orlando Florida

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2008 Spie Defense + Security Presentation

  1. 1. Fixed Analysis Adaptive Synthesis Filter Banks By Clyde A. Lettsome, P.E. Mark J. T. Smith, Ph.D. Russell M. Mersereau, Ph.D.
  2. 2. 2 Outline  Introduction  Time-Varying FIR Filter Banks  Designing The Filters  Results And Conclusions  Future Work
  3. 3. 3 Introduction  Analysis-synthesis filter banks have been employed pervasively in the signal processing community for more than three decades. They are:  Computationally efficient and exactly reconstructing  For image compression the subbands are quantized
  4. 4. 4 Introduction When bit rates are lowered, inevitably distortions occur Challenge: designing of subband image compression systems that can yield improved performance at these lower bit rates.
  5. 5. 5 Time-varying Filter Banks Prior Solution- Time-varying filter banks evolution  Nayebi explored a technique where analysis- synthesis filters are switched to reduce edge distortion.  Arrowood and Sodagar applied Nayebi’s work, investigated post-filtering restore PR.  Time-varying filter banks can reduce the magnitude of these distortions observed at edges in natural images.
  6. 6. 6 Time-varying Filter Banks A disadvantage is that the synthesis filters must be changed in lock step with the analysis filters
  7. 7. 7 Time-varying Filter Banks Analysis Single Set Analysis Multiple Set Synthesis Single Set Numerous Researchers Conventional Filter bank Wavelets No known research done Synthesis Multiple Set Our Research Nayebi, Arrowood, Chung, Sodagar, and others Time-Varying filter banks Newer
  8. 8. 8 Time-varying Filter Banks  Our Solution- Adaptive FIR filter banks for image coding:  have the analysis filters fixed, but the synthesis filters change adaptively,  have no overhead associated with synchronization,  are compatible with existing subband/wavelet encoders.
  9. 9. 9 Time-varying Filter Banks
  10. 10. 10 Designing the Filters
  11. 11. 11 Designing the Filters •Nayebi introduced a time domain formulation that allowed even length FIR filters to be design at a pre- specified system delay.
  12. 12. 12 Designing the Filters An optimization equation is formed using: • reconstruction error component •component associated with the frequency domain characteristics • and a weighting factor
  13. 13. 13 Designing the Filters where
  14. 14. 14 Result and Conclusion Conventional SPIHT Coder Bit Rate: 0.5 bpp PSNR: 31.47 dB Adaptive SPIHT Coder Method applied: Last level of reconstruction Filters used: 9/7 and complementary min and max phase filters Bit Rate: 0.5 bpp PSNR: 32.95 dB
  15. 15. 15 Future Work  Applying technique on more levels  Develop a more sophisticated phase selection approach

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