Impulse Noise Removal from Color Images with Hopfield Neural Network

In this paper, a novel and effective method for impulse noise removal in corrupted color images is discussed. The new method consists of two phases. The first phase is a noise detection phase where a modified Hopfield neural net-work is used to detect impulse noise pixels. The second is a noise filtering phase where the disadvantage of taking Vec-tor Median in a single color space is addressed and a new algorithm based on performing Vector Median first in RGB space and then in HSI space is presented. The results of simulations performed on a set of standard test images on a wide range of noise corruption show that the proposed method is capable of detecting all the impulse noise pix-els with almost zero false positive rates and removes noise while retaining finer image details. It outperforms the stan-dard procedures and is yet simple and suitable for real time applications. 1