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Geometrical-based algorithm for variational segmentation and smoothing of vector-valued images

Lookup NU author(s): Dr Sasan Mahmoodi, Professor Bayan Sharif


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An optimisation method based on a nonlinear functional is considered for segmentation and smoothing of vector-valued images. An edge-based approach is proposed to initially segment the image using geometrical properties such as metric tensor of the linearly smoothed image. The nonlinear functional is then minimised for each segmented region to yield the smoothed image. The functional is characterised with a unique solution in contrast with the Mumford-Shah functional for vector-valued images. An operator for edge detection is introduced as a result of this unique solution. This operator is analytically calculated and its detection performance and localisation are then compared with those of the DroG operator. The implementations are applied on colour images as examples of vector-valued images, and the results demonstrate robust performance in noisy environments. © The Institution of Engineering and Technology 2007.

Publication metadata

Author(s): Mahmoodi S, Sharif BS

Publication type: Article

Publication status: Published

Journal: IET Image Processing

Year: 2007

Volume: 1

Issue: 2

Pages: 112-122

ISSN (print): 1751-9659

ISSN (electronic): 1751-9667

Publisher: The Institution of Engineering and Technology


DOI: 10.1049/iet-ipr:20060218


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