Removal of High Density Impulsive Noise in Image Using Non-linear Filters
Ahmed E.E. Khalil, Samy H. Darwish, Hassan M. A. Elkamchouchi · International Conference on Computational Intelligence, Modelling and Simulation · 2015
Images will pick up noise from a variety of sources that include flecks of dust inside the camera and faulty sensor. One goal in image restoration is to remove the noise from the image where the original image is discernible. This paper presents an overview of effective algorithms in image restoration as untrimmed decision based median filter (UDBMF) and decision based median filter (DBMF). These filters are used and compared with number of existing non linear filters with different levels of noise based on the calculations of mean square error, peak signal to noise ratio, image enhancement factor, mean absolute error, and correlation ratio. The results show that (UDBMF) and (DBMF) can perform better than the other nonlinear filters for noise level up to ninety percent. Also the necessary details in image were preserved.