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

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 Outline
 Introduction
 Time-Varying FIR Filter Banks
 Designing The Filters
 Results And Conclusions
 Future Work

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
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
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
Time-varying Filter Banks
A disadvantage is that the synthesis filters must be
changed in lock step with the analysis filters

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
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
Time-varying Filter Banks

10. 10
Designing the Filters

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
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
Designing the Filters
where

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
Future Work
 Applying technique on more levels
 Develop a more sophisticated phase selection
approach