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Mathematical Problems in Engineering
Volume 2013, Article ID 573941, 8 pages
Research Article

An Adaptive Filtering Algorithm Based on Genetic Algorithm-Backpropagation Network

1Remote Measurement and Control Key Lab of Jiangsu Province, School of Instrument Science & Engineering, Southeast University, Nanjing 210096, China
2School of Information and Control, Nanjing University of Information Science & Technology, Nanjing 210044, China
3Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science & Technology, Nanjing 210044, China

Received 24 December 2012; Accepted 8 March 2013

Academic Editor: Yang Tang

Copyright © 2013 Kai Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A new image filtering algorithm is proposed. GA-BPN algorithm uses genetic algorithm (GA) to decide weights in a back propagation neural network (BPN). It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-BPN to do image noise filter researching work. Firstly, this paper uses training samples to train GA-BPN as the noise detector. Then, we utilize the well-trained GA-BPN to recognize noise pixels in target image. And at last, an adaptive weighted average algorithm is used to recover noise pixels recognized by GA-BPN. Experiment data shows that this algorithm has better performance than other filters.