The discrete time wavelet transform has been used to develop software that detects seismic P and S-phases. The detection algorithm is based on the enhanced amplitude and polarization information provided by the wavele...The discrete time wavelet transform has been used to develop software that detects seismic P and S-phases. The detection algorithm is based on the enhanced amplitude and polarization information provided by the wavelet transform coefficients of the raw seismic data. The algorithm detects phases, determines arrival times and indicates the seismic event direction from three component seismic data that represents the ground displacement in three orthogonal directions. The essential concept is that strong features of the seismic signal are present in the wavelet coefficients across several scales of time and direction. The P-phase is detected by generating a function using polarization information while S-phase is detected by generating a function based on the transverse to radial amplitude ratio. These functions are shown to be very effective metrics in detecting P and S-phases and for determining their arrival times for low signal-to-noise arrivals. Results are compared with arrival times obtained by a human analyst as well as with a standard STA/LTA algorithm from local and regional earthquakes and found to be consistent.展开更多
The process of image compression in a practical Picture Archiving and Communication System (PACS) was discussed with detail. To fully reduce the inter-slice correlation existing in the volumetric image sets generated ...The process of image compression in a practical Picture Archiving and Communication System (PACS) was discussed with detail. To fully reduce the inter-slice correlation existing in the volumetric image sets generated by CT and MR, 3D Discrete Wavelet Transformation (DWT) was introduced in our application. Instead of using a fixed quantizer of lossless low frequency and distinct loss of high frequency, an adaptive quantizer was devised taking MSE as the performance index. In the low frequency subband, DPCM was replaced withS+P transform to facilitate coding computation. Compared with JPEG or 2D DWT, our method is 20%–50% more efficient. Furthermore, preliminary tests showed that 33 dB may be the maximal distortion threshold for CT images.展开更多
文摘The discrete time wavelet transform has been used to develop software that detects seismic P and S-phases. The detection algorithm is based on the enhanced amplitude and polarization information provided by the wavelet transform coefficients of the raw seismic data. The algorithm detects phases, determines arrival times and indicates the seismic event direction from three component seismic data that represents the ground displacement in three orthogonal directions. The essential concept is that strong features of the seismic signal are present in the wavelet coefficients across several scales of time and direction. The P-phase is detected by generating a function using polarization information while S-phase is detected by generating a function based on the transverse to radial amplitude ratio. These functions are shown to be very effective metrics in detecting P and S-phases and for determining their arrival times for low signal-to-noise arrivals. Results are compared with arrival times obtained by a human analyst as well as with a standard STA/LTA algorithm from local and regional earthquakes and found to be consistent.
文摘The process of image compression in a practical Picture Archiving and Communication System (PACS) was discussed with detail. To fully reduce the inter-slice correlation existing in the volumetric image sets generated by CT and MR, 3D Discrete Wavelet Transformation (DWT) was introduced in our application. Instead of using a fixed quantizer of lossless low frequency and distinct loss of high frequency, an adaptive quantizer was devised taking MSE as the performance index. In the low frequency subband, DPCM was replaced withS+P transform to facilitate coding computation. Compared with JPEG or 2D DWT, our method is 20%–50% more efficient. Furthermore, preliminary tests showed that 33 dB may be the maximal distortion threshold for CT images.