NEW ALGORITHM FOR NONLINEAR VECTOR-BASED UP-CONVERSION WITH CENTER WEIGHTED MEDIANS

One important task in the field of digital video signal processing is the conversion of one standard into another with different field and s can rates. Therefore a new vector-based nonlinear upconversion algorit hm has been developed that applies nonlinear center weighted median fi lters (CWM). Assuming a two channel model of the human visual system w ith different spatio-temporal characteristics, there are contrary dema nds for the CWM filters. One can meet these demands by a vertical band separation and an application of so-called temporally and spatially d ominated CWMs. By this means, interpolation errors of the separated ch annels can be compensated by an adequate splitting of the spectrum. Th erefore a very robust vector error tolerant upconversion method can be achieved, which significantly improves the interpolation quality. By an appropriate choice of the CWM filter root structures main picture e lements are interpolated correctly even if faulty vector fields occur. To demonstrate the correctness of the deduced interpolation scheme, p icture content is classified These classes are distinguished by correc t or incorrect vector assignment and correlated or noncorrelated pictu re content. The mode of operation of the new algorithm is portrayed fo r each class. Whereas the mode of operation for correlated picture con tent can be shown by object models, this is shown for noncorrelated pi cture content by the probability distribution function of the applied CWM fillers. The new algorithm has been verified by objective evaluati on methods [peak signal lo noise ratio (PSNR), and subjective mean squ are error (SMSE) measurements] and by a comprehensive subjective test series. (C) 1997 SPIE and IS&T.