文件名称:Pulialroximndi
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Pulse coupled neural network (PCNN) has a specific feature that the fire of
one neuron ca pture its adjacent neurons to fire due to their spatial proximity and
intensity similarity. In this paper, it is indicated that this feature itself is a very good
mechanism for image filtering when the image is damaged with pep and salt (PAS) type
noise. An adaptive filtering method, in which the noisy pixels are first located and then
filtered based on the output of the PCNN, is presented. The threshold function of a neuron
in the PCNN is designed when it is used for filtering random PAS and extreme PAS noise
contaminated image respectively. The filtered image has no distortion for noisy pixels and
only less mistiness for non-noisy pixels, compared with the conventional window-based
filtering method. Excellent experimental results show great effectiveness and efficiency of
the proposed method, especially for heavy-noise contaminated images-Pulse coupled neural network (PCNN) has a specific feature that the fire of
one neuron can capture its adjacent neurons to fire due to their spatial proximity and
intensity similarity. In this paper, it is indicated that this feature itself is a very good
mechanism for image filtering when the image is damaged with pep and salt (PAS) type
noise. An adaptive filtering method, in which the noisy pixels are first located and then
filtered based on the output of the PCNN, is presented. The threshold function of a neuron
in the PCNN is designed when it is used for filtering random PAS and extreme PAS noise
contaminated image respectively. The filtered image has no distortion for noisy pixels and
only less mistiness for non-noisy pixels, compared with the conventional window-based
filtering method. Excellent experimental results show great effectiveness and efficiency of
the proposed method, especially for heavy-noise contaminated images
one neuron ca pture its adjacent neurons to fire due to their spatial proximity and
intensity similarity. In this paper, it is indicated that this feature itself is a very good
mechanism for image filtering when the image is damaged with pep and salt (PAS) type
noise. An adaptive filtering method, in which the noisy pixels are first located and then
filtered based on the output of the PCNN, is presented. The threshold function of a neuron
in the PCNN is designed when it is used for filtering random PAS and extreme PAS noise
contaminated image respectively. The filtered image has no distortion for noisy pixels and
only less mistiness for non-noisy pixels, compared with the conventional window-based
filtering method. Excellent experimental results show great effectiveness and efficiency of
the proposed method, especially for heavy-noise contaminated images-Pulse coupled neural network (PCNN) has a specific feature that the fire of
one neuron can capture its adjacent neurons to fire due to their spatial proximity and
intensity similarity. In this paper, it is indicated that this feature itself is a very good
mechanism for image filtering when the image is damaged with pep and salt (PAS) type
noise. An adaptive filtering method, in which the noisy pixels are first located and then
filtered based on the output of the PCNN, is presented. The threshold function of a neuron
in the PCNN is designed when it is used for filtering random PAS and extreme PAS noise
contaminated image respectively. The filtered image has no distortion for noisy pixels and
only less mistiness for non-noisy pixels, compared with the conventional window-based
filtering method. Excellent experimental results show great effectiveness and efficiency of
the proposed method, especially for heavy-noise contaminated images
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Filtering images contaminated with pep and salt.pdf