Multidimensional Seismic Compression by Hybrid Transform with MultiscaleBased Coding

Amir Z. Averbuch, Valery A. Zheludev and Dan D. Kosloff
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Amir Z. Averbuch: Tel Aviv University, School of Computer Science
Valery A. Zheludev: Tel Aviv University, School of Computer Science
Dan D. Kosloff: Tel Aviv University, Department of Earth and Planetary Sciences

Chapter 43 in Handbook of Geomathematics, 2010, pp 1261-1287 from Springer

Abstract: Abstract We present algorithms that compress two- and three-dimensional seismic data arrays. These arrays are piece-wise smooth in the horizontal directions and have oscillating events in the vertical direction. The transform part of the compression process is an algorithm that combines wavelet and the local cosine transform (LCT). The quantization and the entropy coding parts of the compression were taken from wavelet–based coding such as Set Partitioning in Hierarchical Trees (SPIHT) and Embedded Zerotree Wavelet (EZW) encoding/decoding schemes that efficiently use the multiscale (multiresolution) structure of the wavelet transform coefficients. To efficiently apply these codecs (SPIHT or EZW) to a mixed coefficients array, reordering of the LCT coefficients takes place. This algorithm outperforms other algorithms that are based only on the 2D wavelet transforms. The wavelet part in the mixed transform of the hybrid algorithm utilizes the library of Butterworth wavelets transforms. In the 3D case, the 2D wavelet transform is applied to horizontal planes while the LCT is applied to its vertical direction. After reordering the LCT coefficients, the 3D coding (SPIHT or EZW) is applied. In addition, a 3D compression method for visualization is presented. For this, the data cube is decomposed into relatively small cubes, which are processed separately.

Keywords: Discrete Cosine Transform; Wavelet Coefficient; Discrete Cosine Transform Coefficient; Infinite Impulse Response; Lift Scheme (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1007/978-3-642-01546-5_43

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