A signal-dependent rank ordered mean (SD-ROM) filter-a new approach for removal of impulses from highly corrupted images

Proposes an efficient nonlinear algorithm to suppress impulse noise from highly corrupted images while preserving details and features. The method is applicable to all impulse noise models, including fixed valued (equal height or salt and pepper) impulses and random valued (unequal height) impulses, covering the whole dynamic range. The algorithm is based on a detection-estimation strategy. If a signal sample is detected as a corrupted sample, it is replaced with an estimation of the true value, based on neighborhood information. Otherwise it is kept unchanged. The technique achieves excellent tradeoff between the suppression of noise, and preserving the details and edges without undue increase in computational complexity. Extensive simulation tests indicate that the method performs better than other existing algorithms, including the well known median filters. Illustrative examples included in the paper verify the capability of the proposed approach.