Robust non-linear filtering for video processing

Abstract

Noise removal techniques, such as the K-nearest neighbour filter and the /spl alpha/-trimmed mean filter, are known to be very robust in still image noise removal, but they have not been exploited in video processing. We investigate their 3D-extension for use in video sequence noise removal. We also determine the optimal balance between temporal and spatial window size, the optimal values of the other parameters and finally we investigate the artefacts introduced by the filters. The results show that the new video K-nearest neighbour filter outperforms the video version of the /spl alpha/-trimmed mean and the state-of-the-art rational filter by G. Ramponi from both a PSNR and a visual quality point of view.