Motion-compensated scan conversion of interlaced video sequences
Richard R. Schultz, Robert L. Stevenson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
When an interlaced image sequence is viewed at the rate of sixty frames per second, the human visual system interpolates the data so that the missing fields are not noticeable. However, if frames are viewed individually, interlacing artifacts are quite prominent. This paper addresses the problem of deinterlacing image sequences for the purposes of analyzing video stills and generating high-resolution hardcopy of individual frames. Multiple interlaced frames are temporally integrated to estimate a single progressively-scanned still image, with motion compensation used between frames. A video observation model is defined which incorporates temporal information via estimated interframe motion vectors. The resulting ill- posed inverse problem is regularized through Bayesian maximum a posteriori (MAP) estimation, utilizing a discontinuity-preserving prior model for the spatial data. Progressively- scanned estimates computed from interlaced image sequences are shown at several spatial interpolation factors, since the multiframe Bayesian scan conversion algorithm is capable of simultaneously deinterlacing the data and enhancing spatial resolution. Problems encountered in the estimation of motion vectors from interlaced frames are addressed.