An integrated fuzzy additive and impulse noise reduction method for color images

Noise reduction is a well known problem in image processing. Several filters have already been developed for reducing noise from color images. Since each filter is designed for a particular noise type, these filters reduce only single type of noise. To overcome this drawback, in this paper a new integrated fuzzy filter is presented for the reduction of two types of noise ie) additive noise and impulse noise from digital color images. In the proposed filter an impulse noise detector is used initially to detect the impulse noise present in the filter. Impulse noise detector divides the set of pixels into two point sub-sets: impulse noise contaminated points and clean points without impulse noise. To select the corresponding filters with respect to the noise types, a filter selection module is designed. The filters reduce the noise and the enhanced image is obtained as the output of integrated filter after reducing both the type of noise. The proposed approach combines the advantages of both the additive and impulse noise filter. Experimental and comparison results show that the proposed approach is effective in removing the integrated noise even with severe contamination. The distortions of the microscope that were occurred during the analysis of the structure of tissues, cells and cellular constituents can be reduced using this filter.