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Related papers: Nonlinear Diffusion equations in image processing

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Inverse rendering, the process of inferring scene properties from images, is a challenging inverse problem. The task is ill-posed, as many different scene configurations can give rise to the same image. Most existing solutions incorporate…

Computer Vision and Pattern Recognition · Computer Science 2023-10-03 Linjie Lyu , Ayush Tewari , Marc Habermann , Shunsuke Saito , Michael Zollhöfer , Thomas Leimkühler , Christian Theobalt

Diffusion models are powerful tools for sampling from high-dimensional distributions by progressively transforming pure noise into structured data through a denoising process. When equipped with a guidance mechanism, these models can also…

Machine Learning · Computer Science 2026-05-04 Saeed Mohseni-Sehdeh , Walid Saad , Kei Sakaguchi , Tao Yu

We present a nonlinear dynamical approximation method for time-dependent Partial Differential Equations (PDEs). The approach makes use of parametrized decoder functions, and provides a general, and principled way of understanding and…

Numerical Analysis · Mathematics 2025-05-20 Daan Bon , Benjamin Caris , Olga Mula

This paper investigates solution strategies for nonlinear problems in Hilbert spaces, such as nonlinear partial differential equations (PDEs) in Sobolev spaces, when only finite measurements are available. We formulate this as a nonlinear…

Numerical Analysis · Mathematics 2025-06-06 Daozhe Lin , Qiang Du

Non-linear spectral decompositions of images based on one-homogeneous functionals such as total variation have gained considerable attention in the last few years. Due to their ability to extract spectral components corresponding to objects…

Computer Vision and Pattern Recognition · Computer Science 2020-10-22 Tamara G. Grossmann , Yury Korolev , Guy Gilboa , Carola-Bibiane Schönlieb

We introduce a new numerical strategy to solve a class of oscillatory transport PDE models which is able to captureaccurately the solutions without numerically resolving the high frequency oscillations {\em in both space and time}.Such PDE…

Numerical Analysis · Mathematics 2016-06-01 Nicolas Crouseilles , Shi Jin , Mohammed Lemou

Blind image restoration processors based on convolutional neural network (CNN) are intensively researched because of their high performance. However, they are too sensitive to the perturbation of the degradation model. They easily fail to…

Computer Vision and Pattern Recognition · Computer Science 2018-09-12 Kazutaka Uchida , Masayuki Tanaka , Masatoshi Okutomi

The great advances of learning-based approaches in image processing and computer vision are largely based on deeply nested networks that compose linear transfer functions with suitable non-linearities. Interestingly, the most frequently…

Computer Vision and Pattern Recognition · Computer Science 2018-03-26 Peter Ochs , Tim Meinhardt , Laura Leal-Taixe , Michael Moeller

Inverse problems have many applications in science and engineering. In Computer vision, several image restoration tasks such as inpainting, deblurring, and super-resolution can be formally modeled as inverse problems. Recently, methods have…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Sai Bharath Chandra Gutha , Ricardo Vinuesa , Hossein Azizpour

Partial differential equation (PDE) models are widely used in engineering and natural sciences to describe spatio-temporal processes. The parameters of the considered processes are often unknown and have to be estimated from experimental…

Numerical Analysis · Mathematics 2016-12-21 Romana Boiger , Jan Hasenauer , Sabrina Hross , Barbara Kaltenbacher

Our purpose is to obtain gradient estimates for certain nonlinear partial differential equations by coupling methods. First we derive uniform gradient estimates for a certain semi-linear PDEs based on the coupling method introduced in Wang…

Probability · Mathematics 2014-07-22 Yongsheng Song

Partial differential equations often contain unknown functions that are difficult or impossible to measure directly, hampering our ability to derive predictions from the model. Workflows for recovering scalar PDE parameters from data are…

Machine Learning · Computer Science 2026-02-16 Torkel E. Loman , Yurij Salmaniw , Antonio Leon Villares , Jose A. Carrillo , Ruth E. Baker

In this paper we consider a system of two coupled nonlinear diffusion--reaction partial differential equations (PDEs) which model the growth of biofilm and consumption of the nutrient. At the scale of interest the biofilm density is subject…

Numerical Analysis · Mathematics 2020-01-03 Azhar Alhammali , Malgorzata Peszynska

This paper is concerned with the ubiquitous inverse problem of recovering an unknown function u from finitely many measurements possibly affected by noise. In recent years, inversion methods based on linear approximation spaces were…

Numerical Analysis · Mathematics 2022-10-06 Albert Cohen , Matthieu Dolbeault , Olga Mula , Agustin Somacal

We further develop a new framework, called PDE Acceleration, by applying it to calculus of variations problems defined for general functions on $\mathbb{R}^n$, obtaining efficient numerical algorithms to solve the resulting class of…

Numerical Analysis · Computer Science 2018-10-02 Minas Benyamin , Jeff Calder , Ganesh Sundaramoorthi , Anthony Yezzi

Diffusion-based generative models are a design framework that allows generating new images from processes analogous to those found in non-equilibrium thermodynamics. These models model the reversal of a physical diffusion process in which…

Artificial Intelligence · Computer Science 2023-02-21 Jordi de la Torre

The paper represents the method for construction of the families of particular solutions to some new classes of $(n+1)$ dimensional nonlinear Partial Differential Equations (PDE). Method is based on the specific link between algebraic…

Exactly Solvable and Integrable Systems · Physics 2009-11-10 A. I. Zenchuk

The differential constraints are applied to obtain explicit solutions of nonlinear diffusion equations. Certain linear determining equations with parameters are used to find such differential constraints. They generalize the determining…

Mathematical Physics · Physics 2009-11-07 Oleg V. Kaptsov , Igor V. Verevkin

In this paper, a general model of wireless channels is established based on the physics of wave propagation. Then the problems of inverse scattering and channel prediction are formulated as nonlinear filtering problems. The solutions to the…

Data Analysis, Statistics and Probability · Physics 2015-06-26 Haiqing Wei

In this article, a new method for segmentation and restoration of images on two-dimensional surfaces is given. Active contour models for image segmentation are extended to images on surfaces. The evolving curves on the surfaces are…

Computer Vision and Pattern Recognition · Computer Science 2015-05-04 Heike Benninghoff , Harald Garcke