Abstract
Intersecting cortical model (ICM) has gained widely research as a new artificial neural network. It derives directly from the studies of the small mammal’s visual cortex. The improved extremum and median algorithms can only process the extremum area of image sufficiently. For the non-extremum area of the image, the effect of the improved Extremum-and-Median filter is inadequate. To overcome this shortage, this paper suggests a kind of designing project of the hybrid filter that applied the ideas of the ICM and the improved Extremum-and-Median filter. The theory analysis and the simulation experiments of the image processing indicate that this kind of filter can not only remove noise effectively but also keep the details of the image sufficiently. Moreover, the performance of salt-and-pepper outlier elimination (in super-resolution reconstruction area) based on our hybrid filter also supported our method.




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Acknowledgments
The authors would like to thank the anonymous reviewers for their valuable comments that helped to improve the paper. This work was partly supported by CAS (Chinese Academy of Sciences) Innovation Program Y22114101Q and CAS “100 Talent” Program Y32109101L. This research is also partly supported by the research project for a sustainable development of economic and social structure dependent on the environment of the eastern coast of Asia, by MEXT-Supported Program for the Strategic Research Foundation at Private Universities from 2008 to 2012.
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Zhang, X., Zheng, Z., Asanuma, I. et al. A new kind of hybrid filter based on the intersecting cortical model and the improved Extremum-and-Median filter. Artif Life Robotics 19, 115–119 (2014). https://doi.org/10.1007/s10015-013-0141-x
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DOI: https://doi.org/10.1007/s10015-013-0141-x