Improved tolerance based selective arithmetic mean filter for detection and removal of impulse noise

A superior methodology based on Improved tolerance based selective arithmetic mean filtering technique for the detection and removal of Salt and Pepper Noise on corrupted images is presented in this paper. The function of the proposed filtering technique is to detect and remove the noisy pixels and restore the noise free information. Many linear and non linear filtering techniques have been proposed earlier to remove impulse noise; however the removal of impulse noise is often accomplished at the expense of blurred and distorted features of edges. Therefore it is necessary to preserve the edges and fine details during filtering. Computer simulation is carried out to demonstrate the performance of the proposed techniques and the results show that the proposed Level-2 Improved tolerance based selective arithmetic mean filtering technique (Level-2 ITSAMFT) is superior over the Tolerance based selective arithmetic mean filtering technique (TSAMFT) in maintaining high signal to noise ratio (PSNR), and correlation (COR).