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This paper presents a new approach to image restoration based on ANN, considering the learning of the inverse process using a standard image for training under a multiscale approach. Dierent models of ANN were tested and compared with the traditional techniques. The standard image was articially degraded to simulate some types of frequent degradation problems. Due to the huge amount of data generated for training the ANN, this paper uses clustering techniques to reduce the training set. Thedoi:10.1109/sibgrapi.2009.44 dblp:conf/sibgrapi/CastroSS09 fatcat:lcgzaedinvf7rlsspyldsppzyi