A geometric functional for derivatives approximation

Nir A. Sochen, Robert M. Haralick, Yehoshua Y. Zeevi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We develop on estimation method, for the derivative field of an image based on Bayesian approach which is formulated in a geometric way. The Maximum probability configuration of the derivative field is found by a gradient descent method which leads to a non-linear diffusion type equation with added constraints. The derivatives are assumed to be piecewise smoothe and the Beltrami framework is used in the development of an adaptive smoothing process.

Original languageEnglish
Title of host publicationScale-Space Theories in Computer Vision - 2nd International Conference, Scale-Space 1999, Proceedings
EditorsMads Nielsen, Peter Johansen, Ole Fogh Olsen, Joachim Weickert
PublisherSpringer Verlag
Number of pages6
ISBN (Print)354066498X, 9783540664987
StatePublished - 1999
Externally publishedYes
Event2nd International Conference on Scale-Space Theories in Computer Vision, 1999 - Corfu, Greece
Duration: 26 Sep 199927 Sep 1999

Publication series

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


Conference2nd International Conference on Scale-Space Theories in Computer Vision, 1999


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