Effects of multiple-pass filtering in lossless predictive compression of waveform data

Presents the effects of the predictive filtering of waveform data in multiple passes as the first stage of a two-stage lossless compression algorithm. Predictive compression has a proven track record when applied to high dynamic range waveform data, wherein the waveform data are input to a linear pr...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2002-11, Vol.40 (11), p.2448-2453
Main Authors: Ives, R.W., Magotra, N., Stearns, S.D.
Format: Article
Language:English
Subjects:
Adaptive filters
Applied geophysics
Compressing
Data compression
Decorrelation
Dynamic range
Earth sciences
Earth, ocean, space
Entropy
Event detection
Exact sciences and technology
Filtering
Filtration
Internal geophysics
Longitudinal waves
Lossless
Residues
Signal processing
Signal processing algorithms
Statistics
Waveforms
Wiener filter
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Summary:Presents the effects of the predictive filtering of waveform data in multiple passes as the first stage of a two-stage lossless compression algorithm. Predictive compression has a proven track record when applied to high dynamic range waveform data, wherein the waveform data are input to a linear predictor or perhaps an adaptive predictor for decorrelation, and the resultant residue is then subjected to an entropy coder to (ideally) represent the signal with a minimum number of bits. This compression is commonly applied with no loss of information. In this work, an adaptive filter is used for prediction, but instead of a single run through the predictor, the residue is continually passed back through the predictor in an attempt to further decorrelate the residue. Multiple passes of a gradient adaptive lattice filter has given the best decorrelation, yielding improved compression ratios. We run the compression technique on a seismic database, then provide some comparative lossless compression results using several coding schemes and show that using multiple-pass predictive filtering can improve the compression rates attainable.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2002.805081