DocumentCode :
2151953
Title :
Applying an improved neural network to impulse noise removal
Author :
Deng, Chao ; Liu, Hong-Min ; Wang, Zhi-Heng
Author_Institution :
Coll. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
fYear :
2010
fDate :
11-14 July 2010
Firstpage :
207
Lastpage :
210
Abstract :
A new noise removal algorithm based on improved neural network, is applied to remove the impulse noise of the digital images. First of all, an improved neural network is used to detect the noise-pixels and distinguish it from noise-free pixels efficiently; Second, the noise-pixels are replaced further by the suitable pixel which has the most local similarity; Finally, the output is the combination of the noise-free pixels and the suitable pixel. The proposed algorithm is capable of removing the impulse noise effectively. At the same time it can keep more image details well. Experiential results show that the new algorithm is more improved than the conventional filters.
Keywords :
image denoising; image enhancement; neural nets; digital images; impulse noise removal; neural network; noise free image pixels; noise pixels detection; Algorithm design and analysis; Artificial neural networks; Filtering algorithms; Image restoration; Noise; Optical filters; Pixel; Image enhancement; Image processing; Impulse noise; Local similarity analysis; Neural network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wavelet Analysis and Pattern Recognition (ICWAPR), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6530-9
Type :
conf
DOI :
10.1109/ICWAPR.2010.5576334
Filename :
5576334
Link To Document :
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