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An Improved Fuzzy-based Image Filtering for High Density Salt and Pepper Noise

Yin Mon Swe, Nang Aye Aye Htwe


The proposed system presents a fuzzy switching filter to remove high density salt and pepper noise in an image. This system combined the ability of modified median filter, the proposed fuzzy median filter and the proposed fuzzy mean filter. At first, target pixel in a (3x3) kernel is checked whether it is noise pixel (0 or 255) or not. If there isn’t noise, the noise checking process shifts to the next kernel. If there is noise pixel (0 or 255), the number of noise within a kernel is counted. If the noise count is less than or equal to four which is less noise density, the modified median filter is used to remove noise. If the noise count is greater than four and less than or equal to six, the proposed fuzzy median filter is applied. If the noise count is larger than six which is high noise density, the proposed fuzzy mean filter is used to remove noise. By switching these three filters depending on the noise count within a kernel, the propose system can remove high density salt and pepper noise without distorting the edge and fine details in an image. At the experimental results, the proposed system can give better performance in removing high noise density. Furthermore, the denoising performance of the proposed filters will also be presented by calculating the Peak Signal to Noise Ratio (PSNR) values.


salt and pepper; fuzzy based switching filter; heavy noise density; fuzzy membership function and fuzzy rules

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