@inproceedings{33faaa0b20f84394a6cb139abfdf79a3,
title = "Optimally rotation-equivariant directional derivative kernels",
abstract = "We describe a framework for the design of directional derivative kernels for two-dimensional discrete signals in which we optimize a measure of rotation-equivariance in the Fourier domain. The formulation is applicable to first-order and higher-order derivatives. We design a set of compact, separable, linear-phase derivative kernels of different orders and demonstrate their accuracy.",
author = "Hany Farid and Simoncelli, {Eero P.}",
year = "1997",
doi = "10.1007/3-540-63460-6_119",
language = "English (US)",
isbn = "3540634606",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "207--214",
editor = "Gerald Sommer and Kostas Daniilidis and Josef Pauli",
booktitle = "Computer Analysis of Images and Patterns - 7th International Conference, CAIP 1997, Proceedings",
note = "7th International Conference on Computer Analysis of Images and Patterns, CAIP 1997 ; Conference date: 10-09-1997 Through 12-09-1997",
}