Adaptive seismic compression by wavelet shrinkage

In this paper, a sophisticated adaptive seismic compression method is presented based on wavelet shrinkage. Our approach combines a time-scale transform with an adaptive non-linear statistical method. First, a discrete 2-D biorthogonal discrete wavelet transform (DWT) is applied to the multi-channel...

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Bibliographic Details
Main Author: Khene, M.F. (author)
Other Authors: Abdul-Jauwad, S.H. (author), unknown (author)
Format: article
Published: 2000
Subjects:
Online Access:https://eprints.kfupm.edu.sa/id/eprint/14555/1/14555_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14555/2/14555_2.doc
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Summary:In this paper, a sophisticated adaptive seismic compression method is presented based on wavelet shrinkage. Our approach combines a time-scale transform with an adaptive non-linear statistical method. First, a discrete 2-D biorthogonal discrete wavelet transform (DWT) is applied to the multi-channel seismic signals to generate a sparse multiresolution (subband) decomposition. Compression is then achieved by shrinking the detail wavelet coefficients using a scale-dependent non-linear soft-thresholding rule. The adaptive scale-dependent thresholds are determined by minimizing the Stein's unbiased risk estimate (SURE). The proposed compression procedure is tested on marine seismic data from the Midyan basin (Red Sea, Saudi Arabia)