Efficient Beltrami flow using a short time kernel

Alon Spira*, Ron Kimmel, Nir Sochen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

12 Scopus citations

Abstract

We introduce a short time kernel for the Beltrami image enhancing flow. The flow is implemented by 'convolving' the image with a space dependent kernel in a similar fashion to the implementation of the heat equation by a convolution with a gaussian kernel. The expression for the kernel shows, yet again, the connection between the Beltrami flow and the Bilateral filter. The kernel is calculated by measuring distances on the image manifold by an efficient variation of the fast marching method. The kernel, thus obtained, can be used for arbitrary large time steps in order to produce adaptive smoothing and/or a new scale-space. We apply it to gray scale and color images to demonstrate its flow like behavior.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsLewis D. Griffin, Martin Lillholm
PublisherSpringer Verlag
Pages511-522
Number of pages12
ISBN (Print)354040368X
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2695
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fingerprint

Dive into the research topics of 'Efficient Beltrami flow using a short time kernel'. Together they form a unique fingerprint.

Cite this