A Novel Algorithm of Image Gaussian Noise Filtering based on PCNN Time Matrix

The problem of image Gaussian noise filtering in the framework of Pulse Coupled Neural Network (PCNN) time matrix is addressed. The time matrix, generated by PCNN, contains useful information related to spatial structure of the image under processing. It is a mapping from image spatial information to time sequence. Through time matrix, Gaussian noisy pixels can be detected and then processed by using five methods respectively. Computer simulations show that Gaussian noise can be reduced efficiently, and visual effect of restored images by using the proposed algorithm is much better than those by using traditional noise reduction methods, such as Median Filter, Mean Filter and even Wiener Filter. The proposed algorithm presents higher Peak Signal-to-Noise Ratio, better capability to reduce noise and better protection to edges and details of images. It is a novel Gaussian noise filtering method, which is comparable to Wiener Filter.