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

Abstract

We propose a new approach for motion-compensated, 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 state-transition 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.