This paper addresses an iterative Expectation-Maximization (EM) time-frequency synchronization algorithm joint with channel estimation for MIMO-OFDM systems in frequency selective fading channels. The receivers iterat...
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This paper addresses an iterative Expectation-Maximization (EM) time-frequency synchronization algorithm joint with channel estimation for MIMO-OFDM systems in frequency selective fading channels. The receivers iterates between detection and estimation. For each iteration, we calculate first the expectation of ODFM symbols by using a posteriori probabilities provided by MAP decoder and second we maximise a proposed metric to obtain both frequency offset and then symbol-timing. The channel can be identified by means of these estimates. This algorithm can work in transmission mode and thus can be used to estimate the residual errors or track the change of the parameters. The performance of the proposed synchronization approach, in terms bit error rate and mean square error of the estimated frequency offset, is shown.
Two challenging situations for video frame rate up-conversion (FRUC) are first identified;namely, when the input video has abrupt illumination change and/or a low frame rate. Then, a low-complexity robust FRUC algorit...
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Two challenging situations for video frame rate up-conversion (FRUC) are first identified;namely, when the input video has abrupt illumination change and/or a low frame rate. Then, a low-complexity robust FRUC algorithm is proposed to address these two issues. The proposed algorithm employs a translational motion vector (MV) model of the first- and the second- order and detects the continuity of these motion vectors (MVs). The superior performance of the proposed algorithm has been tested extensively and representative examples are given in this work.
In this paper, we propose a time consistent video segmentation algorithm designed for real-time implementation. Our segmentation algorithm is based on a region merging process that combines both spatial and motion inf...
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In this paper, we propose a time consistent video segmentation algorithm designed for real-time implementation. Our segmentation algorithm is based on a region merging process that combines both spatial and motion information. The spatial segmentation takes benefit of an adaptive decision rule and a specific order of merging. Our method has proven to be efficient for the segmentation of natural images (¤at or textured regions) with few parameters to be set Temporal consistency of the segmentation is ensured by incorporating motion information through the use of an improved changedetection mask. This mask is designed using both illumination differences between frames, and region segmentation of the previous frame. By considering both pixel and region levels, we obtain a particularly efficient algorithm at a low computational cost, allowing its implementation in real-time on the TriMedia processor for CIF image sequences.
To store and retrieve large-scale video data sets effectively, the process of wipe detection is an essential step. In this paper, we propose a wipe scene-changedetection algorithm based on Visual Rhythm Spectrum (VRS...
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To store and retrieve large-scale video data sets effectively, the process of wipe detection is an essential step. In this paper, we propose a wipe scene-changedetection algorithm based on Visual Rhythm Spectrum (VRS). The VRS contains distinctive patterns or visual features for wipe effects. During a wipe, intensity change between incoming and the outgoing shots gives rise to abrupt intensity discontinuities on the VRS. The proposed algorithm is designed to detect such discontinuities.
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