An Adaptive Prediction Filter

1978 ◽  
Author(s):  
Lester M. Bradley ◽  
Federico Salvatti
Keyword(s):  
Adaptive Prediction ◽  
Prediction Filter

A Signal Adaptive Prediction Filter for Video Coding Using Directional Total Variation: Mathematical Framework and Parameter Selection

2020 ◽  
Vol 29 ◽  
pp. 9678-9688
Author(s):  
Jennifer Rasch ◽  
Victor Warno ◽  
Jonathan Pfaff ◽  
Caren Tischendorf ◽  
Detlev Marpe ◽  
...  
Keyword(s):  
Video Coding ◽  
Total Variation ◽  
Parameter Selection ◽  
Mathematical Framework ◽  
Adaptive Prediction ◽  
Prediction Filter

Adaptive prediction filtering in t-x-y domain for random noise attenuation using regularized nonstationary autoregression

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. V13-V21 ◽  
Author(s):  
Yang Liu ◽  
Ning Liu ◽  
Cai Liu
Keyword(s):  
Dimensional Space ◽  
Random Noise ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Noise Attenuation ◽  
Random Noise Attenuation ◽  
Frequency Space ◽  
Adaptive Prediction ◽  
Time Space ◽  
Prediction Filter

Many natural phenomena, including geologic events and geophysical data, are fundamentally nonstationary. They may exhibit stationarity on a short timescale but eventually alter their behavior in time and space. We developed a 2D [Formula: see text] adaptive prediction filter (APF) and further extended this to a 3D [Formula: see text] version for random noise attenuation based on regularized nonstationary autoregression (RNA). Instead of patching, a popular method for handling nonstationarity, we obtained smoothly nonstationary APF coefficients by solving a global regularized least-squares problem. We used shaping regularization to control the smoothness of the coefficients of APF. Three-dimensional space-noncausal [Formula: see text] APF uses neighboring traces around the target traces in the 3D seismic cube to predict noise-free signal, so it provided more accurate prediction results than the 2D version. In comparison with other denoising methods, such as frequency-space deconvolution, time-space prediction filter, and frequency-space RNA, we tested the feasibility of our method in reducing seismic random noise on three synthetic data sets. Results of applying the proposed method to seismic field data demonstrated that nonstationary [Formula: see text] APF was effective in practice.

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