According to the ways to see the real environments, mirror metaphor augmented reality systems can be classified into video see-through virtual mirror displays and reflective half-mirror displays. The two systems have distinctive characteristics and application fields with different types of complexity. In this paper, we introduce a system configuration to implement a prototype of a reflective half-mirror display-based augmented reality system. We also present a two-phase calibration method using an extra camera for the system. Finally, we describe three error sources in the proposed system and show the result of analysis of these errors with several experiments.

Blurred frames may sparsely exist in a video sequence acquired by digital camcorder or digital camera. In order to remove the visually annoying artifact due to those blurred frames, this paper presents a novel motion deblurring algorithm where a blurred frame can be reconstructed utilizing adjacent unblurred frames. Firstly, a motion-compensated predictor of the blurred frame is derived from its neighboring unblurred frame using motion estimation. Then, an accurate blur kernel, which is difficult to obtain from a single blurred frame, is computed using both the predictor and the blurred frame. Next, again using those both frames, a residual deconvolution is proposed to reduce ringing artifacts inherent to conventional deconvolution. Simulation results show that the proposed algorithm provides superior deblurring results over conventional deblurring algorithms while preserving details with reduced ringing artifacts.

This paper proposes a novel de-interlacing algorithm that can make up motion compensation (MC) errors by using maximum likelihood (ML) estimator. Firstly, a proper registration is performed between current field and its adjacent fields, and the progressive frame corresponding to the current field is found via ML estimator based on the computed registration information. Here, in order to obtain a stable solution, well-known bilateral total variation (BTV)-based regularization is applied. Next, possible feathering artifacts are detected on a block basis effectively. So, edge-directional interpolation is applied to the pixels where feathering artifact may happen, instead of the above-mentioned temporal de-interlacing. Experimental results show that the PSNR of our proposed algorithm is on average 4dB higher than that of previous studies and provides the best visual quality.