Rajae Aboulaich, Mohammadia Engineering School (Morocco)

KAUST-IAMCS Workshop on Modeling and Simulation of Wave Propagation and Applications 2012

May 8-9, 2012

King Abdullah University of Science and Technology (KAUST)

Thuwal, Kingdom of Saudi Arabia

A Nash-Game Approach for Image Restoration and Segmentation

Authors:

• Rajae Aboulaich
• Abderrahmane Habbal
• Moez Kallel
• Maher Moakher
  

In this work we propose a game theory approach to simultaneously restore and segment noisy images. We define two players: one is restoration, with the image intensity as strategy, and the other is segmentation with contours as strategy. Cost functions are the classical relevant ones for restoration and segmentation, respectively.

The two players play a static game with complete information, and we consider as solution to the game the so-called Nash Equilibrium. For the computation of this equilibrium we present an iterative method with relaxation. The results of numerical experiments performed on some real images show the relevance and efficiency of the proposed algorithm.

Image segmentation, which is the process of extracting objects from an image, is one of the most important problems in image processing. It has several applications ranging from object recognition, motion detection to medical image analysis. In general, the segmentation of images is a very difficult problem in image processing. For the last few decades, this problem has been formulated as a variational problem leading to partial differential equations.

Most often, the image to be segmented is polluted with noise whose origin can be attributed to the acquisition devices, transmitting channels, random variations in luminosity or temperature during acquisition, etc. It is therefore essential to remove or reduce the noise before segmenting the image. Similar to the image segmentation problem, the restoration of images can be performed using variational methods. We can see [3,4,5,6] for a survey and analysis of the variational methods used in the image restoration and segmentation problems. In what follows we briefly recall some classical variational models used for the restoration, segmentation and joint restoration and segmentation of noisy images.

References:

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