An error concealment method based on Gaussian Mixture Model was proposed to solve the transmission errors of video streaming, and a detailed analysis, demonstration and research were conducted. With the temporal and spatial information adjacent to the lost blocks, an estimation was made of the lost pixel blocks with a minimum mean square error. When some video data were lost,an estimation of the lost pixel blocks with a minimum mean square error based on GMM was proposed. If the temporal information around the lost blocks was also missing, repeated estimation was used to solve the problem. The GMM increased the performance of PSNR compared to previously proposed methods of spatiotemporal error concealment, and the result was valid for a wide range of stationary loss probabilities. Simulations proved that the error concealment method based on GMM was better in enhancing and improving the subjective and objective equality of the video.%把高斯混合模型(GMM)用于视频流的错误隐藏技术中,并对此进行了分析、论证、研究.GMM依据邻近的时域和空域的信息,用最小均方差来估计丢失像素的区域;如部分视频数据丢失,根据丢失视频数据邻近的时-空域信息通过GMM做一个最小均方差估计;如丢失宏块周围的时域信息也随之丢失,则采用反复迭代估计的方法来解决.和现有的基于时-空域的错误隐藏方法相比,基于GMM的错误隐藏方法提高了PSNR,且对于大范围内的丢包率都是有效的.仿真实验也证实了基于GMM的错误隐藏方法能较好地提高和改善视频的主客观质量.
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