New algorithms for recovering highly corrupted images with impulse noise

In this work, we present a new method of noise removal which is applied on images corrupted by impulse noise. This new algorithm has a good trade-off between quantitative and qualitative properties of the recovered image and the computation time. In this new method, the corrupted pixels are replaced by using a median filter or, they are estimated by their neighbors’ values. Our proposed method shows better results especially in very high density noisy images than Standard Median Filter (SMF), Adaptive Median Filter (AMF) and some other well-known filters for removing impulse noise. Experimental results show the superiority of the proposed algorithm in measures of PSNR and SSIM, specifically when the image is corrupted with more than 90% impulse noise.