A noise model based on a wavelet multi-scale expression and its application to the visualization of spatial activity anomalies of earthquakes

A noise model based on an á trous wavelet algorithm produces a multi-scale expression of images through the combination of wavelet transform and a testing model of statistical significance. This kind of expression not only gives the formation and location of image structures in different scales, but also eliminates the influence of noise. Since the algorithm does not need any a priori hypotheses, it is suitable for data with complex structures. The aim of this paper to analyse the spatial activities of earthquakes. Specifically, the method of visualizing the multi-scale spatial activities of earthquakes is discussed in this paper. Taking typical sequences in Southwest China as research cases, we systematically study the structural characteristics of the spatial activities of earthquakes on different scales. The results show that, to some extent, multi-scale spatial structures possess an indicative effect on strong epicenters. The foreshock anomalies of the Songpan seismic sequence also reveal interesting patterns during spatial-temporal evolution.