Mixed-Noise Removal for Color Images Using Modified PCNN Model

Pulse coupled neural networks (PCNN) model is a bionic system. It emulates the behavior of visual cortical neurons of cats and has been extensively applied in image processing areas. A modified PCNN model was designed and applied to mixed-noise removal for color images. The modified model have linear attenuated threshold and weighted averaged gray level output. Hence, it is named as L&A-PCNN. L&A-PCNN model performs much better than other methods in mixed-noise removal for gray level images. In this paper, the L&A-PCNN model is further used to remove mixed-noise of color images by processing each channel of color images individually. Simulation experiments show that the new method improves denoising performance 5% to 30% than current algorithm.