Results 31 to 40 of about 2,210,509 (307)
Seismic Data Denoising Based on Sparse and Low-Rank Regularization
Energies, 2020 Seismic denoising is a core task of seismic data processing. The quality of a denoising result directly affects data analysis, inversion, imaging and other applications.
Shu Li +4 more
doaj +1 more source
Simultaneous Tensor Completion and Denoising by Noise Inequality Constrained Convex Optimization
IEEE Access, 2019 Convex optimization, rather than a non-convex approach, still play important roles in many computer science applications because of its exactness and efficiency.
Tatsuya Yokota, Hidekata Hontani
doaj +1 more source
Gibbs point process approximation: Total variation bounds using Stein's method [PDF]
, 2014 We obtain upper bounds for the total variation distance between the distributions of two Gibbs point processes in a very general setting. Applications are provided to various well-known processes and settings from spatial statistics and statistical ...
Stucki, Kaspar, Schuhmacher, Dominic
core +1 more source
Generalized Hessian-Schatten Norm Regularization for Image Reconstruction
IEEE Access, 2022 Regularization plays a crucial role in reliably utilizing imaging systems for scientific and medical investigations. It helps to stabilize the process of computationally undoing any degradation caused by physical limitations of the imaging process.
Manu Ghulyani +2 more
doaj +1 more source
A Novel Total Variation Model for Low-Dose CT Image Denoising
IEEE Access, 2018 Low-dose computed tomography (LDCT) images are polluted by mottle noise and streak artifacts. To improve LDCT images quality, this paper proposes a novel total variation (NTV) model.
Wenbin Chen +8 more
doaj +1 more source
The Total Variation Flow in RN
Journal of Differential Equations, 2002 In this paper, we study the minimizing total variation flow ut=div(Du/∣Du∣) in N for initial data u0 in Lloc1(N), proving an existence and uniqueness result. Then we characterize all bounded sets Ω of finite perimeter in 2 which evolve without distortion of the boundary.
BELLETTINI G +2 more
openaire +6 more sources
Genetic variation in wholesale carcass cuts predicted from digital images in cattle [PDF]
, 2011 peer-reviewedThe objective of this study was to quantify the genetic variation in carcass cuts predicted using digital image analysis in commercial cross-bred cattle.
W.F. Fikse +11 more
core +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 This article presents a novel global gradient sparse and nonlocal low-rank tensor decomposition model with a hyper-Laplacian prior for hyperspectral image (HSI) superresolution to produce a high-resolution HSI (HR-HSI) by fusing a low-resolution HSI (LR ...
Yidong Peng +3 more
doaj +1 more source
Total-Variation Mode Decomposition [PDF]
, 2021 In this work we analyze the Total Variation (TV) flow applied to one dimensional signals. We formulate a relation between Dynamic Mode Decomposition (DMD), a dimensionality reduction method based on the Koopman operator, and the spectral TV decomposition. DMD is adapted by time rescaling to fit linearly decaying processes, such as the TV flow.
Ido Cohen 0001, Tom Berkov, Guy Gilboa
openaire +1 more source
Non-Quadratic Distances in Model Assessment
Entropy, 2018 One natural way to measure model adequacy is by using statistical distances as loss functions. A related fundamental question is how to construct loss functions that are scientifically and statistically meaningful.
Marianthi Markatou, Yang Chen
doaj +1 more source