Low bit-rate image sequence coding

• Main Author: Cubiss, Christopher
• Published: University of Edinburgh 1994
• Subjects: 502.85
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648984

Digital video, by its very nature, contains vast amounts of data. Indeed, the storage and transmission requirements of digital video frequency far exceed practical storage and transmission capacity. Therefore such research has been dedicated to developing compression algorithms for digital video. This research has recently culminated in the introduction of several standards for image compression. The CCITT H.261 and the motion picture experts group (MPEG) standards both target full-motion video and are based upon a hybrid architecture which combines motion-compensated prediction with transform coding. Although motion-compensated transform coding has been shown to produce <I>reasonable</I> quality reconstructed images, it has also been shown that as the compression ratio is progressively increased the quality of the reconstructed image rapidly degrades. The reasons for this degradation are twofold: firstly, the transform coder is optimised for encoding real-world images, not prediction errors; and secondly, the motion-estimation and transform-coding algorithms both decompose the image into a regular array of blocks which, as the coding distortion is progressively increased, results in the well known 'blocking' effect. The regular structure of this coding artifact makes this error particularly disturbing. This research investigates motion estimation and motion compensated prediction with the aim of characterising the prediction error so that more optimal spatial coding algorithms can be chosen. Motion-compensated prediction was considered in detail. Simple theoretical models of the prediction error were developed and it was shown that, for sufficiently accurate motion estimates, motion-compensated prediction could be considered as a non-ideal spatial band-pass filtering operation. Rate-distortion theory was employed to show that the inverse spectral flatness measure of the prediction error provides a direct indication of the expected coding gain of an optimal hybrid motion-compensated prediction algorithm.