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A Novel Spiking Cortical Model based Filter for Impulse Noise Removal
Author(s) -
Xuming Zhang,
Mingyue Ding,
Yi Zhan,
chaoDou Yang,
pingYin Zhou
Publication year - 2011
Publication title -
international journal of engineering and manufacturing
Language(s) - English
Resource type - Journals
eISSN - 2306-5982
pISSN - 2305-3631
DOI - 10.5815/ijem.2011.02.07
Subject(s) - impulse noise , computer science , median filter , filter (signal processing) , noise (video) , digital filter , pixel , computer vision , salt and pepper noise , artificial intelligence , root raised cosine filter , impulse (physics) , finite impulse response , electronic engineering , algorithm , engineering , image processing , image (mathematics) , physics , quantum mechanics
A novel spiking cortical model based switching mean filter for removing impulse noise is presented. In the proposed filter, the noise detector using spiking cortical model is first adopted to identify the pixels that are likely to be corrupted by impulse noise. Then the detected impulses are removed by the weighted mean filter while the noise-free pixels are left unaltered. Extensive simulations show that the proposed filter outperforms a number of existing decision-based filters due to its excellent performance in terms of effectiveness in image restoration. Because of its outstanding restoration performance, the proposed filter can be used for noise removal in numerous consumer electronics products such as digital camera and digital television.

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