Results 51 to 60 of about 2,330,920 (308)
Non-convex and non-smooth variational decomposition for image restoration
Applied Mathematical Modelling, 2019 The variational image decomposition model decomposes an image into a structural and an oscillatory component by regularization technique and functional minimization.
Liming Tang +3 more
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Parents of children treated for acute lymphoblastic leukemia (ALL) often experience significant caregiver burden and disruption to their well‐being. While parent quality of life (QoL) during treatment is well characterized, little is known about outcomes during early survivorship.
Sara Dal Pra +3 more
wiley +1 more source
Mapping the evolution of mitochondrial complex I through structural variation
FEBS Letters, EarlyView.Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin +2 more
wiley +1 more source
HDR Imaging Based on Low-rank Matrix Completion and Total Variation Constraint [PDF]
Jisuanji gongcheng, 2019 The High Dynamic Range(HDR) imaging method based on Low-rank Matrix Completion(LRMC) removes the ghost image of the moving target in the resulting image by restoring the background information of the moving target occlusion.However,since the model ...
YU Mali,ZHANG Hai
doaj +1 more source
Sparsity Based Methods for Overparameterized Variational Problems
, 2015 Two complementary approaches have been extensively used in signal and image processing leading to novel results, the sparse representation methodology and the variational strategy.
Bruckstein, Alfred M. +2 more
core +1 more source
A variational model in image processing with focal points [PDF]
ESAIM: Mathematical Modelling and Numerical Analysis, 2008 Summary: We propose a model for segmentation problems involving an energy concentrated on the vertices of an unknown polyhedral set, where the contours of the images to be recovered have preferred directions and focal points. We prove that such an energy is obtained as a \(\Gamma\)-limit of functionals defined on sets with smooth boundary that involve ...
BRAIDES, ANDREA, Riey, G.
openaire +2 more sources
Signal Processing, 2018 Non-uniform illumination images are of limited visibility due to under-exposure, over-exposure, or a combination of these two factors. Enhancing these images is a very challenging task in image processing.
Qi-Chong Tian, L. Cohen
semanticscholar +1 more source
FEBS Letters, EarlyView.Fluorescent probes allow dynamic visualization of phosphoinositides in living cells (left), whereas mass spectrometry provides high‐sensitivity, isomer‐resolved quantitation (right). Their synergistic use captures complementary aspects of lipid signaling. This review illustrates how these approaches reveal the spatiotemporal regulation and quantitative
Hiroaki Kajiho +3 more
wiley +1 more source
EURASIP Journal on Image and Video Processing, 2017 A variational Bayesian blind restoration reconstruction based on shear wave transform for low-dose medical computed tomography (CT) image is proposed. The proposed algorithm eliminates the effects of the point spread function in the process of low-dose ...
Yunshan Sun +3 more
doaj +1 more source
A Spatially Adaptive Edge-Preserving Denoising Method Based on Fractional-Order Variational PDEs
IEEE Access, 2020 Image denoising is a basic problem in image processing. An important task of image denoising is to preserve the significant geometric features such as edges and textures while filtering out noise. So far, this is still a problem to be further studied. In
Dehua Wang +3 more
doaj +1 more source