Abstract
Image filtering is able to enhance (or otherwise modify, warp, and mutilate) images and create a new image as a result of processing the pixels of an existing image. Each of pixels in the output image is computed as a function of one or several pixels in the input image, usually located near the output pixel. Different kinds of functions produce different results, and are usually used to remove different noise.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Reference
Gonzalez RC, Woods RE (2002) Digital image processing, 2nd edn. Prentice Hall, Upper Saddle River, NJ.
Ranganath HS, Kuntimad G, Johnson JL (1995) Pulse coupled neural networks for image processing. In: Proceedings of IEEE Southeast Conference, Raleigh, 26–29 March 1995
Zhan K, Zhang HJ, Ma YD (2009) New spiking cortical model for invariant texture retrieval. IEEE Transactions on Neural Networks 20(12): 1980–1986
Ma YD, Shi F, Li L (2003) A new kind of impulse noise filter based on PCNN. In: Proceedings of 2003 International Conference on Neural Networks and Signal Processing, Nanjing, 14–17 December 2003
Ma YD, Zhang HJ (2008) New image denoising algorithm combined PCNN with gray-scale morphology. Journal of Beijing University of Posts and Telecommunications 31(2): 108–112
Ma YD, Zhang HJ (2007) A novel image de-noising algorithm combined ICM with morphology. In: Proceedings of the 7th International Symposium on Communications and Information Technologies, Sydney, 17–19 October 2007
Ma YD, Shi F, Li L (2003) Gaussian noise filter based on PCNN. In: Proceedings of 2003 International Conference on Neural Networks and Signal Processing, Nanjing, 14–17 December 2003
Ma YD, Lin DM, Zhang BD et al (2007) A novel algorithm of image Gaussian noise filtering based on PCNN time matrix. In: Proceedings of IEEE International Conference on Signal Processing and Communication, Dubai, 24–27 November 2007
Lzhikevich EM (1998) Theoretical foundations of pulse-coupled models. In: Proceedings of the 1998 IEEE International Joint Conference on Neural Networks Part 3: IEEE World Congress on Computational Intelligence, Anchorage, 4–9 May 1998
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2010 Higher Education Press, Beijing and Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Ma, Y., Zhan, K., Wang, Z. (2010). Image Filtering. In: Applications of Pulse-Coupled Neural Networks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13745-7_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-13745-7_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13744-0
Online ISBN: 978-3-642-13745-7
eBook Packages: Computer ScienceComputer Science (R0)