Noise robust spatial gradient estimation for use in displacement estimation

James C. Brailean*, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

An important component of any spatial temporal gradient motion estimation algorithm is the accuracy by which spatial gradients are calculated. When an image sequence is corrupted by noise, the problem of determining these spatial gradients becomes extremely difficult. This is immediately apparent, since the magnitude response of the derivative operator is |ωVBAR. In other words, the components of an image are amplified upon differentiation in proportion to their frequency value. Thus, high-frequency noise terms will dominate any low-frequency features in the differentiated image. If this corrupted differentiated image is then used within a spatio-temporal gradient motion estimator, the noise will erroneously influence the estimated motion vector. In this paper, the problem of estimating the spatial gradient is treated as an inverse problem with noise. Formulating the problem in this manner results in a recursive gradient estimator that suppresses the effects of noise.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
Editors Anon
PublisherIEEE
Pages211-214
Number of pages4
Volume1
StatePublished - Jan 1 1996
EventProceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3) - Washington, DC, USA
Duration: Oct 23 1995Oct 26 1995

Other

OtherProceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3)
CityWashington, DC, USA
Period10/23/9510/26/95

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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  • Cite this

    Brailean, J. C., & Katsaggelos, A. K. (1996). Noise robust spatial gradient estimation for use in displacement estimation. In Anon (Ed.), IEEE International Conference on Image Processing (Vol. 1, pp. 211-214). IEEE.