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A novel fast algorithm is suggested for a coding unit (CU) mode decision using pseudo rate‐distortion based on a separated encoding structure in High Efficiency Video Coding (HEVC). A conventional HEVC encoder requires a large computational time for a CU mode prediction because prediction and transformation procedures are applied to obtain a rate‐distortion cost. Hence, for the practical application of HEVC encoding, it is necessary to significantly reduce the computational time of CU mode prediction. As described in this paper, under the proposed separated encoder structure, it is possible to decide the CU prediction mode without a full processing of the prediction and transformation to obtain a rate‐distortion cost based on a suitable condition. Furthermore, to construct a suitable condition to improve the encoding speed, we employ a pseudo rate‐distortion estimation based on a Hadamard transformation and a simple quantization. The experimental results show that the proposed method achieves a 38.68% reduction in the total encoding time with a similar coding performance to that of the HEVC reference model.

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In this paper, we propose the MPEG-7 over MPEG-4 Systems decoder, which compatible with MPEG-4 Systems specification and added MPEG-7 module, which using OCI and MPEG-7 textual descriptor for content search, and it is provides content management and Metadata information.

It is common sense that providing specific odor can increase the video reality when video scene has an object having specific odor. However, people still do not know how to increase video reality and emotional immersion when there is no information on specific odor in the scene. So, present study explores how we improve video reality and immersion when the scene has no concrete odor information from some objects. Especially, this research focuses on diverse previous studies about matching between odor and color and then we expect providing odor can increase video reality if the odor is well-matched with the video's color. To do this, we collected 48 odors and investigated which color was well-matched with each odor. As a result, we get 5 odors which had clearly well-matched colors and decide ill-matched colors of those 5 odors as complementary colors of well-matched colors (Experiment 1). After that, we organize 3 conditions such as coloring image and video clip with well-matched color (color-odor match condition), coloring those with ill-matched color (color-odor mismatch condition), and coloring those with achromatic color by removing color saturation (color-odor neutral condition). Under each of these three conditions, image-odor matching, increment of reality with the odor, increment of immersion with the odor, and odor preference are asked (Experiment 2; 3). The results showed that the scores of all 4 questions in color-odor match condition were higher than color-odor mismatch condition and neutral condition. These results mean that providing matching odor with the scene's color in video is very effective to increase video reality and immersion. We expect experiencing better reality and immersion with olfactory information by adding various future research. 만약