A Variational Model for Joint Motion Estimation and Image Reconstruction

DOI10.1137/16M1084183zbMath1437.94009arXiv1607.03255MaRDI QIDQ4686911

Carola-Bibiane Schönlieb, Martin Burger, Hendrik Meinert Dirks

Publication date: 10 October 2018

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1607.03255

zbMATH Keywords

regularizationimage denoisingmotion estimationdynamic image reconstructionEulerian motion modeljoint variational model

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (14)

Joint reconstruction and low-rank decomposition for dynamic inverse problems ⋮ A new numerical method for level set motion in normal direction used in optical flow estimation ⋮ Task adapted reconstruction for inverse problems ⋮ Using the Navier-Cauchy equation for motion estimation in dynamic imaging ⋮ A Variational Model Dedicated to Joint Segmentation, Registration, and Atlas Generation for Shape Analysis ⋮ A New Variational Model for Joint Image Reconstruction and Motion Estimation in Spatiotemporal Imaging ⋮ Reconstruction Methods in THz Single-Pixel Imaging ⋮ Inertial alternating generalized forward-backward splitting for image colorization ⋮ Template-based image reconstruction from sparse tomographic data ⋮ Statistical model and ML-EM algorithm for emission tomography with known movement ⋮ Joint Motion Estimation and Source Identification Using Convective Regularisation with an Application to the Analysis of Laser Nanoablations ⋮ Enhancing Compressed Sensing 4D Photoacoustic Tomography by Simultaneous Motion Estimation ⋮ Learning optical flow for fast MRI reconstruction ⋮ Spatiotemporal imaging with diffeomorphic optimal transportation

Uses Software

• FlexBox

Cites Work

• Nonlinear total variation based noise removal algorithms
• Regularization of linear inverse problems with total generalized variation
• Compact sets in the space \(L^ p(0,T;B)\)
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Higher-order TV methods -- enhancement via Bregman iteration
• A computational fluid mechanics solution to the Monge-Kantorovich mass transfer problem
• Determining optical flow
• Mathematical Models for Local Nontexture Inpaintings
• The Split Bregman Method for L1-Regularized Problems
• Integral Inequalities of Poincare and Wirtinger Type for BV Functions
• Optimal Control Formulation for Determining Optical Flow
• The Monge–Kantorovitch mass transfer and its computational fluid mechanics formulation
• Computing Optical Flow via Variational Techniques
• Total Generalized Variation
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