School of Information Science and Engineering, Central South University, Changsha, China

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Abstract—Through analysis of PCNN’s work principle, a noval filtering approach capable of detecting and removing impulsive noise in multi-channel images. The filter detects noise pixels in the image by utilizing PCNN’s specific feature that the fire of one neuron can capture firing of its adjacent neurons due to their spatial proximity and intensity similarity. Then it estimates the noise pixels by a VMF-likely vector filtering. Experimental results show that the proposed filter has excellent performance, and is able to preserve fine details while suppressing impulsive noise.

Index Terms—Multi-channel image processing, Nonlinear vector filtering, PCNN.

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Cite: Beiji Zou, Haoyu Zhou, Hao Chen, Cao Shi, "Multi-Channel Image Noise Filter based on PCNN," Journal of Computers vol. 7, no. 2, pp. 475-482, 2012.