Bernoulli Random Undersampling Schemes for 2D Seismic Data Recovery

摘要: Seismic data regularization is an important preprocessing step for seismic signal processing, which has been widely dealt with by compressive sensing recently. Besides sparse representation of in some transform domain and 1-norm reconstruction algorithm, the quality depends greatly on random undersampling schemes. For 2D data, discrete uniform based methods have investigated elaborately. However, designing new schemes still open problem. In this abstract, we propose Bernoulli scheme its jittered version according to distribution law. Experiments Fourier curvelet transforms numerical simulation illustrate that our novel perform better than or as well ones.