Research Workshop 2009/01 - CAPES/COFECUB : Watershed and Image Restoration 

Presenter: André Vital Saúde (UFLA)
Date: 04/08/2009


Image restoration has been frequently treated as a global optimization problem. Usually, the restored image is a function that minimizes the global energy that models the noise. One solution available in the literature is to reduce the energy minimization problem to the problem of finding a minimal cut in a graph, which is a classical problem. After a fine analysis of the minimal cut solution, we propose some greedy assumptions in order to treat the problem as a local optimization problem, and in consequence to obtain a fast algorithm that computes an aproximation of the global minimum. With such greedy assumptions, the image restoration could be computed by watershed-like algorithms. This work is under research. The aim is to share this experience with the colleagues as a way to get feedback about the solution we propose.
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Núcleo de Processamento Digital de Imagens.
Departamento de Ciência da Computação.
Instituto de Ciências Exatas.
Universidade Federal de Minas Gerais



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