IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Synthesis of Gaussian Filters by Cascaded Uniform Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Algorithms for Low-Level Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recursive implementation of the Gaussian filter
Signal Processing
Scale-Space Derived From B-Splines
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Spatio-Frequency Trade-Off Scale for Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gaussian Convolutions. Numerical Approximations Based on Interpolation
Scale-Space '01 Proceedings of the Third International Conference on Scale-Space and Morphology in Computer Vision
Recursive Gaussian Derivative Filters
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
An evaluation of reconstruction filters for volume rendering
VIS '94 Proceedings of the conference on Visualization '94
On the Axioms of Scale Space Theory
Journal of Mathematical Imaging and Vision
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Sampling of periodic signals: a quantitative error analysis
IEEE Transactions on Signal Processing
Hi-index | 0.00 |
Gaussian derivatives are often used as differential operators to analyze the structure in images. In this paper, we will analyze the accuracy and computational cost of the most common implementations for differentiation and interpolation of Gaussian-blurred multi-dimensional data. We show that - for the computation of multiple Gaussian derivatives - the method based on B-splines obtains a higher accuracy than the truncated Gaussian at equal computational cost.