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Bayesian high-resolution reconstruction of low-resolution compressed video

机译:低分辨率压缩视频的贝叶斯高分辨率重建

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A method for simultaneously estimating the high-resolution frames and the corresponding motion field from a compressed low-resolution video sequence is presented. The algorithm incorporates knowledge of the spatio-temporal correlation between low and high-resolution images to estimate the original high-resolution sequence from the degraded low-resolution observation. Information from the encoder is also exploited, including the transmitted motion vectors, quantization tables, coding modes and quantizer scale factors. Simulations illustrate an improvement in the peak signal-to-noise ratio when compared with traditional interpolation techniques and are corroborated with visual results.
机译:呈现了一种用于同时估计来自压缩低分辨率视频序列的高分辨率帧和相应运动场的方法。该算法掺入了低分辨率图像之间的时空相关性的知识,以从降级的低分辨率观察估计原始的高分辨率序列。来自编码器的信息也被利用,包括传输的运动矢量,量化表,编码模式和量化模式尺度因子。模拟与传统的插值技术相比,峰值信噪比的提高,并用视觉结果证实。

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