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<title>Seismic data compression: a comparative study between GenLOT and wavelet compression</title>
Author(s) -
Laurent Duval,
Truong Q. Nguyen
Publication year - 1999
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.366837
Subject(s) - wavelet , filter bank , filter (signal processing) , wavelet transform , data compression , computer science , image compression , coding (social sciences) , raw data , artificial intelligence , algorithm , computer vision , mathematics , image (mathematics) , image processing , statistics , programming language
Generalized Lapped Orthogonal Transform based image coder is used to compress 2D seismic data sets. Its performance is compared to the results using wavelet-based image coder. Both algorithms use the same state-of-the-art zerotree coding for consistency and fair comparison. Several parameters such as filter length and objective cost function are varied to find the best suited filter banks. It is found that for raw data, filter bank with long overlapping filters should be used for processing signals along the time direction whereas filter bank with short filters should be used for processing signal along the distance direction. This combination yields the best results.

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