New flexible segmentation technique in seismic data compression using local cosine transform

Ru-Shan Wu; Yongzhong Wang

doi:10.1117/12.366835

26 October 1999 New flexible segmentation technique in seismic data compression using local cosine transform

Ru-Shan Wu, Yongzhong Wang

Proceedings Volume 3813, Wavelet Applications in Signal and Image Processing VII; (1999) https://doi.org/10.1117/12.366835
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

Best-basis searching algorithm based on binary (in general, M-ary) segmentation was constructed by Coifman and Wickerhauser in 1992. However, there are several problems with the binary scheme. First, the binary segmentation is inflexible in grouping signals along the axis. Secondly, the binary-based segmentation method is very sensitive to time/space shifts of the original signal, such that the resulted best-basis will change a great deal if the signal is shifted by some samples. Thirdly, the reconstruction distortion after compression is relatively strong. In this paper, we design a new flexible segmentation algorithm with arbitrary time/space segmentation resolution which addresses the above-mentioned problems caused by the binary segmentation scheme. This new flexible segmentation algorithm is applied to 2D seismic data compression with two semi-adaptive schemes: Flexible 2D time-ALCT (Adapted Local Cosine Transform) and Flexible 2D space-ALCT. From our numerical tests on both synthetic signals and real seismic data using local cosine transform, the advantages of this new flexible segmentation technique over the binary searching scheme can be easily seen, from overcoming the constraint of dyadic segmentations, reducing time/space- shift sensitivity, less reconstruction distortions to superior performance in seismic data compression.

Citation Download Citation

Ru-Shan Wu and Yongzhong Wang "New flexible segmentation technique in seismic data compression using local cosine transform", Proc. SPIE 3813, Wavelet Applications in Signal and Image Processing VII, (26 October 1999); https://doi.org/10.1117/12.366835

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