Lossless compression of seismic signals using differentiation
- Univ. of Central Florida, Orlando, FL (United States). Dept. of Electrical and Computer Engineering
- Sandia National Labs., Albuquerque, NM (United States)
For some classes of signals, particularly those dominated by low frequency components, such as seismic data, first and higher order differences between adjacent signal samples are generally smaller compared with the signal samples. In this paper, evaluating the differencing approach for losslessly compressing several classes of seismic signals is given. Three different approaches employing derivatives are developed and applied. The performance of the techniques presented here and the adaptive linear predictor are evaluated and compared for the lossless compression of different seismic signal classes. The proposed differentiator approach yields comparable residual energy compared with that obtained employing the linear predictor technique. The two main advantages of the differentiation method are: (1) the coefficients are fixed integers which do not have to be encoded; and (2) greatly reduced computational complexity, relative to the existing algorithms. These advantages are particularly attractive for real time processing. They have been confirmed experimentally by compressing different seismic signals. Sample results including the compression ratio, i.e., the ratio of the number of bits per sample without compression to those with compression using arithmetically encoded residues are also given.
- OSTI ID:
- 207867
- Journal Information:
- IEEE Transactions on Geoscience and Remote Sensing, Journal Name: IEEE Transactions on Geoscience and Remote Sensing Journal Issue: 1 Vol. 34; ISSN IGRSD2; ISSN 0196-2892
- Country of Publication:
- United States
- Language:
- English
Similar Records
Lossless compression of waveform data for efficient storage and transmission
Lossless compression of synthetic aperture radar images