Raymond H. Chan

Department of Mathematics, The Chinese University of Hong Kong

Flexible methodology for image segmentation IP1

In this talk, we introduce a SaT (Smoothing and Thresholding) method for multiphase segmentation of images corrupted with different degradations: noise, information loss and blur. At the first stage, a convex variant of the Mumford-Shah model is applied to obtain a smooth image. We show that the model has unique solution under different degradations. In the second stage, we apply clustering and thresholding techniques to find the segmentation. The number of phases is only required in the last stage, so users can modify it without the need of repeating the first stage again. The methodology can be applied to various kind of segmentation problems, including color image segmentation, hyper-spectral image classification, and point cloud segmentation. Experiments demonstrate that our SaT method gives excellent results in terms of segmentation quality and CPU time in comparison with other state-of-the-art methods. Joint work with: X.H. Cai (UCL), M. Nikolova (ENS, Cachan) and T.Y. Zeng (CUHK)

Chair: Omar Ghattas (The University of Texas at Austin)

The slides are available here

  Tue 05 June at 10:00 Aula Magna (Santa Lucia, floor 0)