Sparse convolution-based digital derivatives, fast estimation for noisy signals and approximation results
From MaRDI portal
Publication:265033
DOI10.1016/j.tcs.2015.12.018zbMath1418.65032OpenAlexW2206739727MaRDI QIDQ265033
Rémy Malgouyres, Henri-Alex Esbelin
Publication date: 1 April 2016
Published in: Theoretical Computer Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.tcs.2015.12.018
Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Numerical differentiation (65D25)
Cites Work
- On the convergence of derivatives of Bernstein approximation
- Convergence of binomial-based derivative estimation for \(C^{2}\) noisy discretized curves
- On the deviation of a parametric cubic spline interpolant from its data polygon
- Curvature estimation along noisy digital contours by approximate global optimization
- Comparison and improvement of tangent estimators on digital curves
- Interval analysis: Theory and applications
- Scale space and PDE methods in computer vision. 5th international conference, Scale-Space 2005, Hofgeismar, Germany, April 7--9, 2005. Proceedings.
- Estimation of the Derivatives of a Digital Function with a Convergent Bounded Error
- Parameter-Free and Multigrid Convergent Digital Curvature Estimators
- About Multigrid Convergence of Some Length Estimators
- Taylor Optimal Kernel for Derivative Etimation
- Robust Geometry Estimation Using the Generalized Voronoi Covariance Measure
- Integral Based Curvature Estimators in Digital Geometry
- Convergence of Level-Wise Convolution Differential Estimators
- Discrete Geometry for Computer Imagery
- Normals and Curvature Estimation for Digital Surfaces Based on Convolutions
- Binomial Convolutions and Derivatives Estimation from Noisy Discretizations
This page was built for publication: Sparse convolution-based digital derivatives, fast estimation for noisy signals and approximation results
