Novel adaptive denoising method for extreme noise based on PCNN

To implement the removal of salt and pepper noise effectively and the conservation of image details and textures, a novel adaptive denoising method for extreme noise based-on pulse coupled neural network(ADEN-PCNN)was proposed. A kind of detection mechanism was applied to discriminate whether a given pixel was corrupted or not, and only the corrupted pixels must be denoised so that the original image information could not be damaged and the details as well as the textures of the images clould be conserved effectively. To improve the image quality, the self-organization mechanism was introduced into PCNN array framework, thus the neighboring connection modes of neurons in the PCNN could switch automatically. Furthermore, an adaptive mechanism was used to automatically select the optimal filtering times based on the estimated noise intensity to enhance adaptability of algortihm. Experiment results indicate that this method presented is more preponderant than the conventional methods and other congeneric methods in removing noise and conserving image details.