Research on Spatially Selective Noise Filtration based WaveletTransform
Around the problem that the wavelet transform modulus maxima de-noising method algorithm has an inferior stability as well as a large number of calculations ,another de noising method based on transmission characteristics of wavelet transform at different scales is discussed——spatially selective noise filtration based on wavelet transform (Spatially Selective Noise Filtration, SNNF) . However, in some cases, SSNF algorithm for de-noising has a common effect. This is because the use of mask filter only filters out the noise where the scale value is relatively small, but leaves the noise where the scale value is relatively big. In addition, the noise included in the most low-frequency component is not yet filtered out in the original algorithm, in view of the above factors, the original algorithm is improved and the mean filters of the various scales and the most low-frequency component are carried out prior to wavelet reconstruction. The improved algorithm is applied to the actual seismic signal process, and the results show the effect of the improved SNNF algorithm.
seismic signal noise Spatially Selective Noise Filtration wavelet transform
Yao Jianhong Liu Jicheng
The School of Electric and Information Engineering, DaQing Petroleum Institute, DaQing, 163318, China
国际会议
长沙
英文
2482-2485
2010-05-11（万方平台首次上网日期，不代表论文的发表时间）