A new motion-compensated reduced-order model Kalman filter for space-varying restoration of progressive and interlaced video

We propose a new approach for motioncompensated, reduced-order model Kalman filtering for restoration of progressive and interlaced video. In the case of interlaced inputs, the proposed filter also performs deinterlacing. In contrast to the literature, both motion-compensation and reduced-order state modeling are achieved by augmenting the observation equation, as opposed to modifying the statetransition equation. The proposed modeling, which includes the two-dimensional (2-D) reduced order model Kalman filtering (ROMKF) of Angwin and Kaufman as a special case, results in significant performance improvement in fixed-lag Kalman filtering of space-varying blurred images. This is demonstrated by experimental results.