Results 21 to 30 of about 19,283,190 (228)
Global Total Variation Minimization [PDF]
SIAM Journal on Numerical Analysis, 1999 Summary: The minimization of the total variation is an important tool of image processing. A lot of authors have addressed the problem and developed algorithms for image denoising. In this paper we present an alternative approach of the total variation minimization problem.
Dibos, Françoise, Koepfler, Georges
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Hyperspectral Image Superresolution Using Unidirectional Total Variation With Tucker Decomposition
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 The hyperspectral image superresolution (HSI-SR) problem aims to improve the spatial quality of a low spatial resolution HSI by fusing the LR-HSI with the corresponding high spatial resolution multispectral image.
Ting Xu +4 more
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Airborne Radar Super-Resolution Imaging Based on Fast Total Variation Method
Remote Sensing, 2021 Total variation (TV) is an effective super-resolution method to improve the azimuth resolution and preserve the contour information of the target in airborne radar imaging.
Qiping Zhang +4 more
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Remote Sensing, 2018 Exploration of multiple priors on observed signals has been demonstrated to be one of the effective ways for recovering underlying signals. In this paper, a new spectral difference-induced total variation and low-rank approximation (termed SDTVLA) method
Le Sun +4 more
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IEEE Access, 2020 The fusion of hyperspectral and multispectral images is an effective way to obtain hyperspectral super-resolution images with high spatial resolution. A hyperspectral image is a datacube containing two spatial dimensions and a spectral dimension.
Fei Ma, Feixia Yang, Yanwei Wang
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Signals, 2023 In this paper, we propose robust image-smoothing methods based on ℓ0 gradient minimization with novel gradient constraints to effectively suppress pseudo-edges. Simultaneously minimizing the ℓ0 gradient, i.e., the number of nonzero gradients in an image,
Ryo Matsuoka, Masahiro Okuda
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On the total variation of the Jacobian
Journal of Functional Analysis, 2004 Let \(\Omega\) be an open subset of \({\mathbb R}^2\), and \(u=(u^1,u^2)\in L^\infty_{\text{ loc}}(\Omega;{\mathbb R}^2)\cap W^{1,p}(\Omega;{\mathbb R}^2)\) for some \(p>1\). In the paper, a comparison is carried out among the classical Jacobian determinant \(\det Du\) defined a.e. in \(\Omega\), the distributional Jacobian determinant \(\text{ Det} Du\
I. FONSECA, N. FUSCO, MARCELLINI, PAOLO
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Journal of Mathematical Imaging and Vision, 2017 Discretization schemes commonly used for total variation regularization lead to images that are difficult to interpolate, which is a real issue for applications requiring subpixel accuracy and aliasing control. In the present work, we reconciliate total variation with Shannon interpolation and study a Fourier-based estimate that behaves much better in ...
Abergel, Rémy, Moisan, Lionel
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Sparse View CT Image Reconstruction Based on Total Variation and Wavelet Frame Regularization
IEEE Access, 2020 The sparse view problem of image reconstruction encountered in computed tomography (CT) is an important research issue due to its considerable potential in lowering radiation dose.
Zhaoyan Qu +3 more
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Uneven Index: A Digital Biomarker to Prompt Demodex Blepharitis Based on Deep Learning
Frontiers in Physiology, 2022 Purpose: To evaluate ocular surface manifestations and morphological changes in meibomian glands (MGs) based on artificial intelligence (AI) analysis in patients with Demodex blepharitis.Methods: In this retrospective study, 115 subjects were enrolled ...
Xinyi Liu +12 more
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