Compression schemes based on Discrete Wavelet Transform (DWT) have been compared at different seismic processing stages. To evaluate the performances of the lossy compression algorithm an objective test set (whiteness set) has been introduced to quantify the effects on the reconstructed data. High compression rates (up to 40:1 and beyond) may be achieved by optimizing the multidimensional filter bank, quantizer and coder, and the seismic pre-processing (e.g., NMO correction and gain). The effects of different compression algorithms (both filter and quantizer implementation) have been investigated at different processing stages using the whiteness test set.
Lossy compression of seismic data based on the X2-T Discrete Wavelet Transform
V Rampa;
1999
Abstract
Compression schemes based on Discrete Wavelet Transform (DWT) have been compared at different seismic processing stages. To evaluate the performances of the lossy compression algorithm an objective test set (whiteness set) has been introduced to quantify the effects on the reconstructed data. High compression rates (up to 40:1 and beyond) may be achieved by optimizing the multidimensional filter bank, quantizer and coder, and the seismic pre-processing (e.g., NMO correction and gain). The effects of different compression algorithms (both filter and quantizer implementation) have been investigated at different processing stages using the whiteness test set.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
