Nonlinear optimisation method for image segmentation and noise reduction using geometrical intrinsic properties
Mahmoodi, Sasan and Sharif, Bayan (2006) Nonlinear optimisation method for image segmentation and noise reduction using geometrical intrinsic properties. Image and Vision Computing, 24, 202-209.
- Published Version
This paper considers the optimisation of a nonlinear functional for image segmentation and noise reduction. Equations optimising this functional are derived and employed to detect edges using geometrical intrinsic properties such as metric and Riemann curvature tensor of a smooth differentiable surface approximating the original image. Images are then smoothed using a Helmholtz type partial differential equation. The proposed approach is shown to be very efficient and robust in the presence of noise, and the reported results demonstrate better performance than the conventional derivative based edge detectors.
|Keywords:||Optimisation; Edge detection; Noise reduction; Partial differential equations; Differential geometry|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||09 Jun 2008 12:30|
|Last Modified:||20 Aug 2012 04:28|
|Contributors:||Mahmoodi, Sasan (Author)
Sharif, Bayan (Author)
|Further Information:||Google Scholar|
|ISI Citation Count:||4|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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