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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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Fixed Analysis Adaptive Synthesis
Filter Banks
ByClyde A. Lettsome, P.E.Mark J. T. Smith, Ph.D.
Russell M. Mersereau, Ph.D.
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 more than three decades. They are:
Computationally efficient and exactly reconstructing
For image compression the subbands are quantized
4
Introduction
When bit rates are lowered, inevitably distortions occurChallenge: designing of subband image compression systems that can yield improved performance at these lower bit rates.
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
Time-varying Filter Banks
A disadvantage is that the synthesis filters must be changed in lock step with the analysis filters
7
Time-varying Filter Banks
AnalysisSingle Set
AnalysisMultiple Set
SynthesisSingle Set
Numerous ResearchersConventional Filter bankWavelets
No known research done
SynthesisMultiple Set
Our Research Nayebi, Arrowood, Chung, Sodagar, and othersTime-Varying filter banksNewer
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
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 a pre-specified system delay.
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 Designing the Filters
where
14Result 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
Future Work
Applying technique on more levels Develop a more sophisticated phase selection
approach
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