Noise reduction of severely corrupted image sequences

A nonlinear adaptive noise filter for filtering the nonstationary signals from image sequences is presented. The filter uses estimates of the local statistics to adapt instantaneously. The authors propose to use a robust recursive estimator for those statistics which is based on order statistics. Prior to filtering, motion is estimated from the sequence and compensated for. For the estimation, a recursive block-matcher is used with a match criterion based on higher order statistics. By weighing out outlier data, this estimator provides robust estimates. The overall combination is able adequately to remove severe noise while maintaining sharp results. The computational complexity makes the method suitable for off-line processing only.<>