DocumentCode :
2819490
Title :
Image Denoising Based on Combined Neural Networks Filter
Author :
Junhong Chen ; Qinyu Zhang
Author_Institution :
Shenzhen Grad. Sch., Dept. of Electron. & Inf. Eng., Harbin Inst. of Technol., Shenzhen, China
fYear :
2009
fDate :
19-20 Dec. 2009
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, a new image restoration method based on combined neural networks Alter is proposed. This combined neural networks Alter is posed by a BPNN Alter and an image data fusion system based on self-organizing mapping neural networks. And this approach can use the corrupted image itself as training data to avoid the problem of how to choose the training data, which is most of the other neural networks denoising methods have to face, by using the distributed character of WGN. Experiment results show that the proposed method can denoise the noises effectively.
Keywords :
filtering theory; image denoising; image restoration; self-organising feature maps; sensor fusion; Alter; image data fusion system; image denoising; image restoration; neural networks filter; self-organizing mapping neural networks; Digital filters; Digital images; Image denoising; Image restoration; Information filtering; Information filters; Neural networks; Noise reduction; Training data; White noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
Type :
conf
DOI :
10.1109/ICIECS.2009.5363487
Filename :
5363487
Link To Document :
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