A new kind of hybrid filter based on the intersecting cortical model and the improved Extremum-and-Median filter
Intersecting cortical model (ICM) has gained widely research as a new artificial neural network. It derives directly from the studies of the small mammals visual cortex. The improved extremumand 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.
intersecting cortical model nonlinear filter median filter cubic spline interpolation