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