In this paper a new filter for image sequences corrupted with random impulse noise is presented. In order to preserve the image details as much as possible, the noise is removed in different successive filtering steps. In each step, only the pixels that are detected as being noisy are filtered, while the noise-free pixels remain unchanged. The noise detection is based on fuzzy set theory and fuzzy rules, which are very useful for the processing of human knowledge and linguistic values. To exploit the temporal information in image sequences as much as possible, detected pixels are finally filtered in a motion compensated way. From the experimental results it can be seen that the proposed method outperforms other state-of-the-art filters both in terms of the peak-signal-to-noise ratio, the mean absolute error, and visually.
Etienne E. Kerre,
"Random impulse noise removal from image sequences based on fuzzy logic," Journal of Electronic Imaging 20(1), 013024 (1 January 2011). https://doi.org/10.1117/1.3564922