Variational methods for normal integration
From MaRDI portal
Publication:1636005
DOI10.1007/s10851-017-0777-6zbMath1420.94019arXiv1709.05965OpenAlexW2755753771MaRDI QIDQ1636005
Yvain Quéau, Jean-François Aujol, Jean-Denis Durou
Publication date: 1 June 2018
Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1709.05965
variational methodsintegrationphotometric stereoshape-from-shadinggradient fieldnormal field3D-reconstruction
Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Numerical methods of relaxation type (49M20)
Related Items (2)
Normal integration: a survey ⋮ A linearization-based hybrid approach for 3D reconstruction of objects in a single image
Uses Software
Cites Work
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nonlinear total variation based noise removal algorithms
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Convex image denoising via non-convex regularization with parameter selection
- iPiasco: inertial proximal algorithm for strongly convex optimization
- A dual algorithm for the solution of nonlinear variational problems via finite element approximation
- Nonlinearities and noise reduction in 3-source photometric stereo
- Normal integration: a survey
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Fast and accurate surface normal integration on non-rectangular domains
- Regularized reconstruction of a surface from its measured gradient field
- A TGV-Based Framework for Variational Image Decompression, Zooming, and Reconstruction. Part I: Analytics
- iPiano: Inertial Proximal Algorithm for Nonconvex Optimization
- Variational Analysis in Sobolev and BV Spaces
- Optimal approximations by piecewise smooth functions and associated variational problems
- The Split Bregman Method for L1-Regularized Problems
- Approximation of functional depending on jumps by elliptic functional via t-convergence
- Edge-Preserving Integration of a Normal Field: Weighted Least-Squares, TV and $$L^1$$ Approaches
- Direct analytical methods for solving Poisson equations in computer vision problems
- The variational approach to shape from shading
- Image Selective Smoothing and Edge Detection by Nonlinear Diffusion
- A Note on the Ratio of Two Normally Distributed Variables
- Atomic Decomposition by Basis Pursuit
- Active contours without edges
- An Algebraic Multigrid Approach for Image Analysis
- Local Strong Homogeneity of a Regularized Estimator
- Image Segmentation by Variational Methods: Mumford and Shah Functional and the Discrete Approximations
- Rate of Convergence Analysis of Decomposition Methods Based on the Proximal Method of Multipliers for Convex Minimization
- Fast Alternating Direction Optimization Methods
- How to Choose Interpolation Data in Images
- A Nearly-m log n Time Solver for SDD Linear Systems
This page was built for publication: Variational methods for normal integration
