Journal ArticleDOI
Adaptive filtering of random noise in near-surface seismic and ground-penetrating radar data
TLDR
In this paper, two adaptive algorithms, the optimum 2D median filter and the 2D adaptive Wiener filter, were designed by adopting adaptive algorithms to suppress speckle noise in 2D digital image data.About:
This article is published in Journal of Applied Geophysics.The article was published on 2009-05-01. It has received 34 citations till now. The article focuses on the topics: Adaptive filter & Median filter.read more
Citations
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Journal ArticleDOI
Comparisons of wavelets, contourlets and curvelets in seismic denoising
TL;DR: In this article, a combination scheme of wavelets and curvelets is applied to seismic random denoising by solving an l 1 norm optimization problem, and the combined scheme aims at taking advantage of the respective merits of wavelet and curvelet in order to obtain better effects.
Journal ArticleDOI
Poststack Seismic Data Denoising Based on 3-D Convolutional Neural Network
TL;DR: Wang et al. as mentioned in this paper designed an end-to-end 3D denoising convolutional neural network (3-D-DnCNN) that takes raw 3D cubes as input in order to better extract the features of the 3-D spatial structure of post-stack seismic data.
Journal ArticleDOI
Material Classification of Underground Utilities From GPR Images Using DCT-Based SVM Approach
TL;DR: Simulation results show that the proposed technique combined with adaptive Wiener filter reveals a good performance regarding the recognition accuracy compared to the other studied techniques in noisy environment.
Journal ArticleDOI
Nonlinear data processing method for the signal enhancement of GPR data
Chih Sung Chen,Yih Jeng +1 more
TL;DR: An alternative data processing procedure is proposed for enhancing the signal/noise (S/N) ratio of ground penetrating radar (GPR) data by performing the logarithmic transform in conjunction with the ensemble empirical mode decomposition (EEMD), a new nonlinear data analysis method in signal processing.
References
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Book
Adaptive Filter Theory
TL;DR: In this paper, the authors propose a recursive least square adaptive filter (RLF) based on the Kalman filter, which is used as the unifying base for RLS Filters.
Journal ArticleDOI
Digital Image Enhancement and Noise Filtering by Use of Local Statistics
TL;DR: Experimental results show that in most cases the techniques developed in this paper are readily adaptable to real-time image processing.
Book
Two-Dimensional Signal and Image Processing
TL;DR: This text covers the principles and applications of "multidimensional" and "image" digital signal processing and is suitable for Sr/grad level courses in image processing in EE departments.