A median/ANFIS filter for efficient restoration of digital images corrupted by impulse noise
A new operator for removing impulse noise from digital images is presented. The proposed operator is a hybrid filter constructed by combining four center-weighted median filters (CWMF) with a simple adaptive neuro-fuzzy inference system (ANFIS). The internal parameters of the ANFIS are optimized by training. The training is performed by using simple artificial images which can easily be generated by computer. The fundamental advantage of the proposed operator over other operators in the literature is that it efficiently removes impulse noise while at the same time effectively preserves image details and texture. Performance of the proposed operator is tested at various noise densities and for different test images, and also compared with conventional as well as state-of-the-art impulse noise removal operators. Experimental results show that the proposed operator significantly outperforms the other operators and efficiently removes impulse noise from digital images without distorting image details and texture.
median filter image processing noise filtering neuro-fuzzy systems