Recently, high definition media services like HDTV and IPTV are growing. A fast reduced-size image extracting method is required to meet what those services require. Conventional DC image extracting methods, however, can't be applied to H.264/AVC streams since a spatial domain prediction scheme is adopted in H.264/AVC intra mode. To solve this problem, a thumbnail extraction method in H.264/AVC was proposed. However, the method has mismatch problem which was caused by round-off operation in intra prediction and mismatch between integer and floating point calculation. In this paper, we propose an error compensation method for extracting thumbnail directly in H.264/AVC bitstreams. The compensation method introduces the mismatch problem in thumbnail extraction and presents compensation values. Through the implementation and performance evaluation, proposed method compensated round-off error efficiently in D1 and HD sequences while the additional extraction time is negligible.
This paper presents a vote decision-based deinterlacing scheme for false directional error correction(VDD) to convert interlaced signal into non-interlaced signal using only one fields. The VDD using the vote decision goes through four steps process . The first step extracts regions having doubt of false edge using MM-ELA method. In these regions, the edge direction is decided by the majority vote using upper adjacent pixels's information through the second step. But, we still have undecided directions, which will be decided by the majority vote and the directional average decision at the third step. This step preserves the edge directions and minimizes visual degradation. Finally, the last step interpolates undecided pixels using DOI method which can consider the fine edge direction. Although the VDD with hierarchical structure has a high complexity, it can extract delicate edge compared to other pixel-by-pixel or window-by-window deinterlacing algorithms. Simulation results show that it has significantly improved both the subjective and objective qualities of the reconstructed images.
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