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相关论文: A variational approach to nonlocal image restorati…

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We consider a one-dimensional nonlocal nonlinear equation of the form: $\partial_t u = (\Lambda^{-\alpha} u)\partial_x u - \nu \Lambda^{\beta}u$ where $\Lambda =(-\partial_{xx})^{\frac 12}$ is the fractional Laplacian and $\nu\ge 0$ is the…

偏微分方程分析 · 数学 2012-07-05 Hongjie Dong , Dong Li

The total variation (TV) flow generates a scale-space representation of an image based on the TV functional. This gradient flow observes desirable features for images, such as sharp edges and enables spectral, scale, and texture analysis.…

计算机视觉与模式识别 · 计算机科学 2024-04-23 Tamara G. Grossmann , Sören Dittmer , Yury Korolev , Carola-Bibiane Schönlieb

We prove space and time regularity for solutions of fully nonlinear parabolic integro-differential equations with rough kernels. We consider parabolic equations $u_t = \I u$, where $\I$ is translation invariant and elliptic with respect to…

偏微分方程分析 · 数学 2014-04-17 Joaquim Serra

In this paper, we propose a variational approach based on optimal transportation to study the existence and unicity of solution for a class of parabolic equations involving $q(x)$-Laplacian operator \begin{equation*}\label{equation variable…

偏微分方程分析 · 数学 2020-01-01 Aboubacar Marcos , Ambroise Soglo

We study well-posedness of degenerate mixed-type parabolic-hyperbolic equations $$ \partial_tu+\textrm{div}\big(f(u)\big)=\mathcal{L}[b(u)] $$ on bounded domains with general Dirichlet boundary/exterior conditions. The nonlocal diffusion…

偏微分方程分析 · 数学 2025-09-24 Jørgen Endal , Espen R Jakobsen , Ola Mæhlen

Using a calibration method we prove that, if $\Gamma\subset \Omega$ is a closed regular hypersurface and if the function $g$ is discontinuous along $\Gamma$ and regular outside, then the function $u_{\beta}$ which solves $$ \begin{cases}…

泛函分析 · 数学 2007-05-23 Massimiliano Morini

We establish existence of travelling waves to the gradient system $u_t = u_{zz} - \nabla W(u)$ connecting two minima of $W$ when $u : \R \times (0,\infty) \larrow \R^N$, that is, we establish existence of a pair $(U,c) \in [C^2(\R)]^N \by…

经典分析与常微分方程 · 数学 2011-06-07 N. I. Katzourakis , N. D. Alikakos

We consider four prototypes of variational problems and prove the existence of fractal minimizers through the direct method in the calculus of variations. By design these minimizers are H\"older curves or H\"older parametrizations of…

概率论 · 数学 2025-12-17 Michael Hinz , Jonas M. Tölle , Lauri Viitasaari

We consider the partial differential equation $$ u-f={\rm div}\left(u^m\frac{\nabla u}{|\nabla u|}\right) $$ with $f$ nonnegative and bounded and $m\in\mathbb{R}$. We prove existence and uniqueness of solutions for both the Dirichlet…

偏微分方程分析 · 数学 2019-07-23 Lorenzo Giacomelli , Salvador Moll , Francesco Petitta

Underwater images are typically characterized by color cast, haze, blurring, and uneven illumination due to the selective absorption and scattering when light propagates through the water, which limits their practical applications.…

计算机视觉与模式识别 · 计算机科学 2024-07-23 Yuemei Li , Guojia Hou , Peixian Zhuang , Zhenkuan Pan

In this paper we study the following class of fractional relativistic Schr\"odinger equations: \begin{equation*} \left\{ \begin{array}{ll} (-\Delta+m^{2})^{s}u + V(\varepsilon x) u= f(u) &\mbox{ in } \mathbb{R}^{N}, \\ u\in…

偏微分方程分析 · 数学 2023-03-24 Vincenzo Ambrosio

We study the uniqueness, existence, and properties of bounded distributional solutions of the initial value problem problem for the anomalous diffusion equation $\partial_tu-\mathcal{L}^\mu [\varphi (u)]=0$. Here $\mathcal{L}^\mu$ can be…

偏微分方程分析 · 数学 2016-09-20 Félix del Teso , Jørgen Endal , Espen R. Jakobsen

A variational model for imaging segmentation and denoising color images is proposed. The model combines Meyer's "u+v" decomposition with a chromaticity-brightness framework and is expressed by a minimization of energy integral functionals…

偏微分方程分析 · 数学 2016-03-25 Rita Ferreira , Irene Fonseca , M. Luisa Mascarenhas

This paper deals with the following fractional Choquard equation $$\varepsilon^{2s}(-\Delta)^su +Vu=\varepsilon^{-\alpha}(I_\alpha*|u|^p)|u|^{p-2}u\ \ \ \mathrm{in}\ \mathbb{R}^N,$$ where $\varepsilon>0$ is a small parameter, $(-\Delta)^s$…

偏微分方程分析 · 数学 2023-02-24 Yinbin Deng , Shuangjie Peng , Xian Yang

We discuss a variational approach to doubly nonlinear wave equations of the form $\rho u_{tt} + g (u_t) - \Delta u + f (u)=0$. This approach hinges on the minimization of a parameter-dependent family of uniformly convex functionals over…

偏微分方程分析 · 数学 2024-01-18 Goro Akagi , Verena Bögelein , Alice Marveggio , Ulisse Stefanelli

Modeling magnitude Magnetic Resonance Images (MRI) rician denoising in a Bayesian or generalized Tikhonov framework using Total Variation (TV) leads naturally to the consideration of nonlinear elliptic equations. These involve the so called…

偏微分方程分析 · 数学 2018-11-27 Adrian Martin , Emanuele Schiavi , Sergio Segura de Leon

In this paper we consider the problem of minimizing functionals of the form $E(u)=\int_B f(x,\nabla u) \,dx$ in a suitably prepared class of incompressible, planar maps $u: B \rightarrow \mathbb{R}^2$. Here, $B$ is the unit disk and…

偏微分方程分析 · 数学 2024-09-10 Marcel Dengler , Jonathan J. Bevan

This paper establishes a complete homogenization theory for the one-dimensional parabolic equation with long-range correlated random potential: \[ \partial_t u_\varepsilon(t,x) = \frac{1}{2} \partial_{xx} u_\varepsilon(t,x) +…

概率论 · 数学 2025-12-10 Atef Lechiheb

Diffusion models have emerged as a key pillar of foundation models in visual domains. One of their critical applications is to universally solve different downstream inverse tasks via a single diffusion prior without re-training for each…

机器学习 · 计算机科学 2023-10-03 Morteza Mardani , Jiaming Song , Jan Kautz , Arash Vahdat

Ultra-high-definition (UHD) image deblurring poses significant challenges for UHD restoration methods, which must balance fine-grained detail recovery and practical inference efficiency. Although prominent discriminative and generative…

计算机视觉与模式识别 · 计算机科学 2026-03-12 Yucheng Xin , Dawei Zhao , Xiang Chen , Chen Wu , Pu Wang , Dianjie Lu , Guijuan Zhang , Xiuyi Jia , Zhuoran Zheng