Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

TLDR: This scheme can remove salt-and-pepper-noise with a noise level as high as 90% and show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only.

Abstract: This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.