A new image sequence coding technique based on robust median-based predictors is presented for the transmission of image sequences over noisy channels. We analyze the robustness of median-based predictors against channel errors. A heuristic algorithm for the design of a robust predictor from a given median-based predictor is presented. It is shown that with small modifications in terms of a necessary requirement for a median-based predictor to be robust against channel errors, the robustness of a given median-based predictor can be considerably improved. Simulations on a real image sequence show significant improvement over the conventional differential pulse code modulation (DPCM) at high bit error rate (BER) using this new technique. The technique does not increase the transmission rate. It is shown that the quality of reconstructed images obtained by robust median-based predictors can be further improved by postprocessing the image using a nonlinear detail-preserving noise-smoothing filter.

Most current algorithms developed for image sequence filtering require motion information in order to obtain good results both in the still and moving parts of an image sequence. In the present paper, filters which completely preserve stationary regions in image sequences are introduced. In moving regions, the 3D filters inherently reduce to spatial filters and perform well in these areas without any motion-compensation or motion-detection. A new multivariate filtering operation called the alpha-trimmed vector median is proposed. Guidelines for the determination of optimal 3D median-related structures for color and gray-level image sequence filtering are given. Algorithms based on vector median, extended vector median, alpha-trimmed vector median, and componentwise median operations are developed. Properties of the human visual system are taken into account in the design of filters. Noise attenuation and detail preservation capability of the filters is examined. In particular, the impulsive noise attenuation capability of the filters is analyzed theoretically. Simulation results based on real image sequences are given.>