Improved Picture Rate Conversion Using Classification Based LMS- Filters

Due to the recent explosion of multimedia formats and the need to convert between them, more attention is drawn to picture rate conversion. Moreover, growing demands on video motion portrayal without judder or blur requires improved format conversion. The simplest conversion repeats the latest picture until a more recent one becomes available. Advanced methods estimate the motion of moving objects to interpolate their correct position in additional images. Although motion blur and judder have been reduced using motion compensation, artifacts, especially around the moving objects in sequences with fast motion, may be disturbing. Previous work has reduced this so-called „halo‟ artifact, but the overall result is still perceived as sub-optimal due to the complexity of the heuristics involved. In this paper, we aim at reducing the heuristics by designing LMS up conversion filters optimized for pre-defined local spatio-temporal image classes. Design and evaluation, and a benchmark with earlier techniques will be discussed. In general, the proposed approach gives better results.