Format

Send to

Choose Destination
See comment in PubMed Commons below
IEEE Trans Image Process. 2004 Apr;13(4):496-508.

Differentiation of discrete multidimensional signals.

Author information

1
Computer Science Department, Dartmouth College, Hanover, NH 03755, USA. farid@cs.dartmouth.edu

Abstract

We describe the design of finite-size linear-phase separable kernels for differentiation of discrete multidimensional signals. The problem is formulated as an optimization of the rotation-invariance of the gradient operator, which results in a simultaneous constraint on a set of one-dimensional low-pass prefilter and differentiator filters up to the desired order. We also develop extensions of this formulation to both higher dimensions and higher order directional derivatives. We develop a numerical procedure for optimizing the constraint, and demonstrate its use in constructing a set of example filters. The resulting filters are significantly more accurate than those commonly used in the image and multidimensional signal processing literature.

PMID:
15376584
[Indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Loading ...
    Support Center