Results 11 to 20 of about 37,700 (292)
SIMRES-TV: NOISE AND RESIDUAL SIMILARITY FOR PARAMETER ESTIMATION IN TOTAL VARIATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 Image restoration with regularization models is very popular in the image processing literature. Total variation (TV) is one of the important edge preserving regularization models used, however, to obtain optimal restoration results the regularization ...
V. B. S. Prasath +6 more
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An augmented Lagrangian method for solving total variation (TV)-based image registration model [PDF]
Journal of Algorithms & Computational Technology, 2020 Variational methods for image registration basically involve a regularizer to ensure that the resulting well-posed problem admits a solution. Different choices of regularizers lead to different deformations.
Noppadol Chumchob, Ke Chen
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Image denoising via a non-local patch graph total variation.
PLoS ONE, 2019 Total variation (TV) based models are very popular in image denoising but suffer from some drawbacks. For example, local TV methods often cannot preserve edges and textures well when they face excessive smoothing.
Yan Zhang +4 more
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Deflection Tomography Reconstruction Based on Diagonal Total Variation
MATEC Web of Conferences, 2018 In view of the shortages of the reconstruction algorithm based on Total Variation (TV) minimum under the framework of measured field compressed sensing, we study the measured field sparse representation method and solving method of optimization equation,
Li Huaxin, Pan Jinxiao
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral image (HSI) denoising remains challenging due to the difficulty in recovering the complex structure in HSIs under the corruption of mixed-noise. Existing methods face two key limitations: 1) they ignore the underlying structural information,
Ke Yang +6 more
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A four directions variational method for solving image processing problems [PDF]
Iranian Journal of Numerical Analysis and Optimization, 2020 In this paper, based on a discrete total variation model, a modified discretization of total variation (TV) is introduced for image processing problems.
Alireza H., E.E. Esfahani
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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
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Collaborative Total Variation: A General Framework for Vectorial TV Models [PDF]
SIAM Journal on Imaging Sciences, 2016 Even after over two decades, the total variation (TV) remains one of the most popular regularizations for image processing problems and has sparked a tremendous amount of research, particularly to move from scalar to vector-valued functions. In this paper, we consider the gradient of a color image as a three dimensional matrix or tensor with dimensions
Joan Duran +3 more
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On the total variation Wasserstein gradient flow and the TV-JKO scheme [PDF]
ESAIM: Control, Optimisation and Calculus of Variations, 2019 We study the JKO scheme for the total variation, characterize the optimizers, prove some of their qualitative properties (in particular a form of maximum principle and in some cases, a minimum principle as well). Finally, we establish a convergence result as the time step goes to zero to a solution of a fourth-order nonlinear evolution equation, under ...
Carlier, Guillaume, Poon, Clarice
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Applied Mathematics in Science and Engineering, 2023 Full waveform inversion (FWI) can provide an accurate velocity model by matching observed and simulated seismograms. Mathematically, FWI is a highly ill-posed inverse problem that the observed data are independent of the model and cannot be inverted ...
Hongsun Fu, Hongyu Qi, Ruixue Gu
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