Journal ArticleDOI
Noise reduction by vector median filtering
TLDR
In this paper, an extension of the scalar median filter to a vector median filter (VMF) was proposed for suppressing noise contained in geophysical data represented by multidimensional, multicomponent vector fields.Abstract:
The scalar median filter (SMF) is often used to reduce noise in scalar geophysical data. We present an extension of the SMF to a vector median filter (VMF) for suppressing noise contained in geophysical data represented by multidimensional, multicomponent vector fields. Although the SMF can be applied to each component of a vector field individually, the VMF is applied to all components simultaneously. Like the SMF, the VMF intends to suppress random noise while preserving discontinuities in the vector fields. Preserving such discontinuities is essential for exploration geophysics because discontinuities often manifest important geologic features such as faults and stratigraphic channels. The VMF is applied to synthetic and field data sets. The results are compared to those generated by using SMF, f-x deconvolution, and mean filters. Our results indicate that the VMF can reduce noise while preserving discontinuities more effectively than the alternatives. In addition, a fast VMF algorithm is descr...read more
Citations
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Journal ArticleDOI
In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level
Katie McDole,Léo Guignard,Fernando Amat,Andrew B. Berger,Grégoire Malandain,Loic Royer,Srinivas C. Turaga,Kristin Branson,Philipp J. Keller +8 more
TL;DR: A light-sheet microscope is developed that adapts itself to the dramatic changes in size, shape, and optical properties of the post-implantation mouse embryo and captures its development from gastrulation to early organogenesis at the cellular level.
Journal ArticleDOI
Iterative deblending of simultaneous-source seismic data using seislet-domain shaping regularization
TL;DR: In this article, a novel iterative estimation scheme for separation of blended seismic data from simultaneous sources is proposed based on an augmented estimation problem that can be solved by iteratively constraining the deblended data using shaping regularization in the seislet domain.
Journal ArticleDOI
Damped multichannel singular spectrum analysis for 3D random noise attenuation
TL;DR: In this paper, a damping factor was introduced into traditional multichannel singular spectrum analysis (MSSA) to dampen the singular values to distinguish between signal and noise in seismic data.
Journal ArticleDOI
Deep denoising autoencoder for seismic random noise attenuation
Omar M. Saad,Yangkang Chen +1 more
TL;DR: The proposed algorithm to attenuate random noise based on a deep-denoising autoencoder (DDAE) succeeds in attenuating the random noise in an effective manner and is compared with several benchmark algorithms.
References
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Journal ArticleDOI
Vector median filters
TL;DR: In this article, two nonlinear algorithms for processing vector-valued signals are introduced, called vector median operations, which are derived from two multidimensional probability density functions using the maximum-likelihood-estimate approach.
Journal ArticleDOI
Fast structural interpretation with structure-oriented filtering
TL;DR: This paper addresses a new approach to structural interpretation of 3-D seismic data by changing from a one-time transmission of final results to a repetitive process of feeding data into iterative team processes—starting with a crude structural model and followed by increasingly detailed, sophisticated models.
Journal ArticleDOI
Fast structural interpretation with structure-oriented filteringStructure-Oriented Filtering
Journal ArticleDOI
Robust estimates of 3D reflector dip and azimuth
TL;DR: In this article, a more robust estimation of dip and azimuth leads to increased resolution of well-established algorithms such as coherence, coherent amplitude gradients, and structurally oriented filtering.
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