Optimized wavelet-based satellite image de-noising with multi-population differential evolution-assisted harris hawks optimization algorithm
In this research, we propose to utilize the newly introduced Multi-population differential
evolution-assisted Harris Hawks Optimization Algorithm (CMDHHO) in the optimization …
evolution-assisted Harris Hawks Optimization Algorithm (CMDHHO) in the optimization …
Unsupervised seismic random noise attenuation based on deep convolutional neural network
Random noise attenuation is one of the most essential steps in seismic signal processing.
We propose a novel approach to attenuate seismic random noise based on deep …
We propose a novel approach to attenuate seismic random noise based on deep …
基于fx域TV正则化的共偏移距道集随机噪声压制方法
石战战， 庞溯， 王元君， 池跃龙， 周强 - 地球物理学进展, 2022 - dzkx.org
fx 域去噪假设空间方向上任意单频信号具有可预测性, 当处理叠前去共炮点道集和共中心点道集
时会损害倾斜同相轴, 原因是fx 域去噪基于线性常倾角和平稳假设. 提出基于fx 域TV …
时会损害倾斜同相轴, 原因是fx 域去噪基于线性常倾角和平稳假设. 提出基于fx 域TV …
S2S-WTV: Seismic data noise attenuation using weighted total variation regularized self-supervised learning
Seismic data often undergo severe noise due to environmental factors, which seriously
affect subsequent applications. Traditional hand-crafted denoisers such as filters and …
affect subsequent applications. Traditional hand-crafted denoisers such as filters and …
Improved low-rank tensor approximation for seismic random plus footprint noise suppression
Random plus footprint noise provokes severe seismic image deterioration and makes it
challenging for interpreters to recognize and analyze accurate subsurface responses. Thus …
challenging for interpreters to recognize and analyze accurate subsurface responses. Thus …
Unsupervised erratic seismic noise attenuation with robust deep convolutional autoencoders
F Qian, W Guo, Z Liu, H Yu, G Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Erratic seismic noise, following a (known or unknown) non-Gaussian distribution, poses a
formidable challenge to conventional methods of random noise attenuation. Many erratic …
formidable challenge to conventional methods of random noise attenuation. Many erratic …
Ground truth-free 3-D seismic random noise attenuation via deep tensor convolutional neural networks in the time-frequency domain
The inherent challenge of 3-D seismic noise attenuation is determining how to uncover high-
dimensional concise structures that only exist in true signals to eliminate random noise. The …
dimensional concise structures that only exist in true signals to eliminate random noise. The …
A sparse model-inspired deep thresholding network for exponential signal reconstruction—Application in fast biological spectroscopy
The nonuniform sampling (NUS) is a powerful approach to enable fast acquisition but
requires sophisticated reconstruction algorithms. Faithful reconstruction from partially …
requires sophisticated reconstruction algorithms. Faithful reconstruction from partially …
Random noise attenuation in seismic data using Hankel sparse low-rank approximation
The Hankel matrix's low-rank property derived from the noise-free seismic data describing a
few linear events and has been successively leveraged in many low-rank seismic data de …
few linear events and has been successively leveraged in many low-rank seismic data de …
Statistics-guided dictionary learning for automatic coherent noise suppression
Y Zhou, J Yang, H Wang, G Huang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Coherent seismic noise is usually difficult to attenuate due to the similar morphological
patterns between noise and useful signals. To attenuate coherent noise, special …
patterns between noise and useful signals. To attenuate coherent noise, special …