Impulse Noise Removal from Color Images with Hopfield Neural Network and Improved Vector Median Filter
G. Phani Deepti, Maruti V Borker, Jayanthi Sivaswamy · 2008
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 network is used to detect impulse noise pixels. The second is a noise filtering phase where the disadvantage of taking vector 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 pixels with almost zero false positive rates and removes noise while retaining finer image details. It outperforms the standard procedures and is yet simple and suitable for real time applications.