Weighted Fuzzy Mean Filters For Image Processing

A New fuzzy filter for the removal of heavy additional impulse noise called the Weighted Fuzzy Mean (WFM) filter is proposed. In this WFM filter we generate five fuzzy sets for an image such as dark (DK), median (MD), bright (BR), very dark(VDK) and very bright (VBR). The WFM-filtered output signal is the mean value of the corrupted signals in a sample matrix and these signals are weighted by a membership grade of an associated fuzzy set stored in a knowledge base. The knowledge base contains a number of fuzzy sets decided by experts or derived from the histogram of a reference image. When noise probability exceeds 0.3, WFM gives very superior performance compared with conventional filters when evaluated by mean square error (MSE), peak signal-to- noise-rate (PSNR). In this mean filter we are using the method fuzzy logic. This splits the image in to blocks. By comparing the pixel value in the each block we can increase the resolution of the image based on the SNR values.