Lossless compression of waveform data for efficient storage and transmission

Journal Article · Sat May 01 00:00:00 EDT 1993 · IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States)

DOI:https://doi.org/10.1109/36.225531· OSTI ID:6245978

Stearns, S D ^[1]; Tan, Li Zhe; Magotra, Neeraj ^[2]

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1. Sandia National Lab., Albuquerque, NM (United States)
2. Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering

Compression of waveform data is significant in many engineering and research areas since it can be used to alleviate data storage and transmission bandwidth. For example, seismic data are widely recorded and transmitted so that analysis can be performed on large amounts of data for numerous applications such as petroleum exploration, determination of the earth's core structure, seismic event detection and discrimination of underground nuclear explosions, etc. This paper describes a technique for lossless wave form data compression. The technique consists of two stages. The first stage is a modified form of linear prediction with discrete coefficients and the second stage is bi-level sequence coding. The linear predictor generates an error or residue sequence in a way such that exact reconstruction of the original data sequence can be accomplished with a simple algorithm. The residue sequence is essentially white Gaussian with seismic or other similar waveform data. Bi-level sequence coding, in which two sample sizes are chosen and the residue sequence is encoded into subsequences that alternate from one level to the other, further compresses the residue sequence. The principal feature of the two-stage data compression algorithm is that it is lossless, that is, it allows exact, bit-for-bit recovery of the original data sequence. The performance of the lossless compression algorithm at each stage is analyzed. The advantages of using bi-level sequence coding in the second stage are its simplicity of implementation, its effectiveness on data with large amplitude variations, and its near-optimal performance in encoding Gaussian sequences. Applications of the two-stage technique to typical seismic data indicates that an average number of compressed bits per sample close to the lower bound is achievable in practical situations.

• OSTI ID: 6245978
• Journal Information: IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States), Journal Name: IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers); (United States) Vol. 31:3; ISSN IGRSD2; ISSN 0196-2892
• Country of Publication: United States
• Language: English

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