Impulsive Noise Removal based on Neural Network Schemes
Pages: 76 - 89
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Participants:
Turki Y. Abdalla |
Abdul-Kareem Younis |
Sarah Behnam Aziz |
Summary:
Interest in neural networks as an alternative to conventional algorithmic techniques has grown rapidly in recent years. Noise removal or noise suppression is an important task in image processing. In general, the results of the noise removal have a strong influence on the quality of the following image processing techniques. In this paper, two feed-forward NNs schemes have been presented for impulsive noise removal. The computation is reduced by using an artificial image in training. Results of NN schemes show high performance especially when the ratio of impulsive noise in testing is the same or greater than that of the training image. The presented schemes are used for grayscale and also for true color.