High density salt-and-pepper noise suppression using adaptive dual threshold decision based algorithm in fingerprint images

In this paper, we will propose an efficient technique using adaptive dual threshold decision based algorithm for removing of salt and pepper noise in different fingerprint images. In the first step, the recent adaptive dual threshold is applied to detect the pixels which are likely to be corrupted more efficiently. In the second step, only the corrupted pixels are replaced by the decision based algorithm value in filter window. The quality of fingerprint images denoising is studied. It is shown that the new scheme is significantly better with the peak signal to noise ratio (PSNR) when compared to some recently published method. Also, it will establish in improving performance of removing salt and pepper noise.