Wednesday, 1 February 2017

Using Center Weighted Mean Filter Technique for Removal of Impulse and Pepper Noise

Impulse noise and Pepper Noise often disturbed Digital images. In Image and Video Processing System, The most common and important processing operation is image denoising. There are so many linier and non linier filtering algorithm are proposed in literature for image denoising.
For visual perception image edges and details carry
very important information and have high frequency. in digital image filtering we need good edges and image detail properties which is highly suitable for filters. Sharp edges are generally disturbed by linier filters. It also destroy lines and other fine details which present in the image. A search for non linier filter alternatives has been led by filters.    
To remove high density noise in images are presented we need some improved decision based nonlinear edge preserving algorithms. For suppressing different types of noise in the image with good edge and fine detail preserving characteristics, the proposed filters are simple and effective. A decision based adaptive recursive weighted mean filter is proposed; the filter uses the mean controlled algorithm for weight
calculation. A decision based adaptive window scheme is incorporated in the recursive weighted mean filter. The proposed filter is shown to be effective in removing high density salt and pepper noise quite well with edge preservation.

The proposed Modified Decision Based UnsymmetricTrimmed Mean Filter (MDBUTMF) algorithm processes the corrupted images by first detecting the impulse noise. The processing pixel is checked whether it is noisy or noisy free. That is, if the processing pixel lies between maximum and minimum gray level values then it is noise free is left unchanged.If the processing pixel takes the maximum or minimum gray level then it is noisy pixel which is processed by MDBUTMF.

                                                                                                                      Neeraj Sharma
                                                                                                                   Assistant Professor
                                                                                                 Parishkar college of Global Excellence

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