Results 1 to 10 of about 17,556,704 (381)
Kernel Estimation Using Total Variation Guided GAN for Image Super-Resolution [PDF]
Sensors, 2023 Various super-resolution (SR) kernels in the degradation model deteriorate the performance of the SR algorithms, showing unpleasant artifacts in the output images. Hence, SR kernel estimation has been studied to improve the SR performance in several ways
Jongeun Park, Hansol Kim, Moon Gi Kang
doaj +2 more sources
Multiclass Total Variation Clustering [PDF]
, 2013 Ideas from the image processing literature have recently motivated a new set of clustering algorithms that rely on the concept of total variation.
Bresson, Xavier +3 more
core +6 more sources
SIAM Journal on Imaging Sciences, 2016 We consider the problem of minimizing the continuous valued total variation subject to different unary terms on trees and propose fast direct algorithms based on dynamic programming to solve these problems.
Kolmogorov, Vladimir +2 more
core +3 more sources
Copy Number Variation Detection Using Total Variation. [PDF]
ACM BCB, 2019 Next-generation sequencing (NGS) technologies offer new opportunities for precise and accurate identification of genomic aberrations, including copy number variations (CNVs). For high-throughput NGS data, using depth of coverage has become a major approach to identify CNVs, especially for whole exome sequencing (WES) data.
Zare F, Nabavi S.
europepmc +4 more sources
CMOS Fixed Pattern Noise Elimination Based on Sparse Unidirectional Hybrid Total Variation [PDF]
Sensors, 2020 With the improvement of semiconductor technology, the performance of CMOS Image Sensor has been greatly improved, reaching the same level as that of CCD in dark current, linearity and readout noise. However, due to the production process, CMOS has higher
Tao Zhang +3 more
doaj +2 more sources
, 2012 Publication in the conference proceedings of EUSIPCO, Bucharest, Romania ...
İlker Bayram, Mustafa E. Kamaşak
openalex +3 more sources
Weighted Group Sparsity-Constrained Tensor Factorization for Hyperspectral Unmixing
Remote Sensing, 2022 Recently, unmixing methods based on nonnegative tensor factorization have played an important role in the decomposition of hyperspectral mixed pixels.
Xinxi Feng, Le Han, Le Dong
doaj +1 more source
Deep Unfolding Network for Multi-Band Images Synchronous Fusion
IEEE Access, 2023 This study proposes a new deep neural network to solve the multi-band image synchronous fusion problem (MBF-Net). Unlike other deep learning-based methods, our network architecture design combines the ideas of model-driven and data-driven methods, so it ...
Dong Yu +4 more
doaj +1 more source
Superresolution of Radar Forward-Looking Imaging Based on Accelerated TV-Sparse Method
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Total variation-sparse (TV-sparse)-based multiconstraint devonvolution method has been used to realize superresolution imaging and preserve target contour information simultaneously of radar forward-looking imaging.
Yin Zhang +4 more
doaj +1 more source
Total roto-translational variation [PDF]
Numerische Mathematik, 2019 We consider curvature depending variational models for image regularization, such as Euler's elastica. These models are known to provide strong priors for the continuity of edges and hence have important applications in shape-and image processing. We consider a lifted convex representation of these models in the roto-translation space: In this space ...
Chambolle, Antonin, Pock, Thomas
openaire +4 more sources