小波
箱子
质心
噪音(视频)
计算机科学
统计
算法
数学
人工智能
图像(数学)
作者
Senlin Yang,Jinghuai Gao,Wenchao Chen,Daxing Wang,Bin Weng
摘要
We compare four Q‐factor estimation methods, including logarithmic spectral ratio (LSR), centroid frequency shifting (CFS), peak frequency shifting (PFS), and wavelet envelope peak instantaneous frequency (WEPIF) methods. First of all, principals of these four methods for Q‐factor estimation are described briefly. Then some performances are compared for them with wavelet independence, noise resistance, and resolution of thin beds. For different source wavelets, LSR method works well; WEPIF method has slight wavelet dependence; CFS and PFS methods have strong wavelet dependence. For random noise, Q‐factors estimated by CFS and PFS methods show bigger errors and instability, and Q‐factors estimated by LSR and WEPIF methods give small relative error and good stability for seismic data of high signal‐to‐noise ratio (SNR). The synthetic test of a wedge model indicates that CFS method produces the lowest resolution, LSR and PFS methods demonstrate a moderate high resolution, and WEPIF method provides the highest resolution. Taking aspects compared above into consideration, the WEPIF method is relatively better than other three methods in some extent.
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