Results 51 to 60 of about 17,556,704 (381)
Learning Consistent Discretizations of the Total Variation
SIAM Journal of Imaging Sciences, 2020 In this work, we study a general framework of discrete approximations of the total variation for image reconstruction problems. The framework, for which we can show consistency in the sense of Γ-convergence, unifies and extends several existing ...
A. Chambolle, T. Pock
semanticscholar +1 more source
On-the-fly Approximation of Multivariate Total Variation Minimization [PDF]
, 2016 In the context of change-point detection, addressed by Total Variation minimization strategies, an efficient on-the-fly algorithm has been designed leading to exact solutions for univariate data.
Abry, Patrice +3 more
core +2 more sources
IEEE Access, 2020 Blind image inpainting is a challenging task in image processing. Motivated by the excellent performance of low dimensional manifold model (LDMM) in image inpainting for large-scale pixels missing, we introduce a novel blind inpainting model to repair ...
Mei Gao +4 more
doaj +1 more source
A Two-Staged Feature Extraction Method Based on Total Variation for Hyperspectral Images
Remote Sensing, 2022 Effective feature extraction (FE) has always been the focus of hyperspectral images (HSIs). For aerial remote-sensing HSIs processing and its land cover classification, in this article, an efficient two-staged hyperspectral FE method based on total ...
Chunchao Li +4 more
doaj +1 more source
Entropy, 2020 We consider a sub-class of the f-divergences satisfying a stronger convexity property, which we refer to as strongly convex, or κ-convex divergences. We derive new and old relationships, based on convexity arguments, between popular f-divergences.
James Melbourne
doaj +1 more source
Remote Sensing, 2020 The total variation (TV) method has been applied to realizing airborne scanning radar super-resolution imaging while maintaining the outline of the target.
Xingyu Tuo +3 more
doaj +1 more source
Weighted and Well-Balanced Nonlinear TV-Based Time-Dependent Model for Image Denoising
Chaos Theory and Applications, 2023 The partial differential equation (PDE)-based models are widely used to remove additive Gaussian white noise and preserve edges, and one of the most widely used methods is the total variation denoising algorithm.
Khursheed Alam +2 more
doaj +1 more source
Total variation error bounds for geometric approximation
, 2013 We develop a new formulation of Stein's method to obtain computable upper bounds on the total variation distance between the geometric distribution and a distribution of interest.
Peköz, Erol A. +2 more
core +2 more sources
Hyperspectral Feature Extraction Using Sparse and Smooth Low-Rank Analysis
Remote Sensing, 2019 In this paper, we develop a hyperspectral feature extraction method called sparse and smooth low-rank analysis (SSLRA). First, we propose a new low-rank model for hyperspectral images (HSIs) where we decompose the HSI into smooth and sparse components ...
Behnood Rasti +2 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Pediatric patients with extracranial solid tumors (ST) receiving chemotherapy are at an increased risk for Pneumocystis jirovecii pneumonia (PJP). However, evidence guiding prophylaxis practices in this population is limited. A PJP‐related fatality at our institution highlighted inconsistent prescribing approaches and concerns about
Kriti Kumar +8 more
wiley +1 more source