在视频通信中，由于信道噪声的影响，致使视频图象中经常出现比特差错以及块和宏块差错，它们严重地影响着视频的质量，同时由于基于检错重发的机制不能很好地满足实时的要求，目前许多人提出了时域、空域、频域以及它们的联合差错消除方法，但这些方法比较复杂，为了利用简单可行的方法，在校正错误的同时，并能满足实时传输处理的要求，从而提出了一种基于不同频率成分的空域误码隐匿和恢复方法，该方法利用马尔科夫随机场描述了像素之间以及像素块之间的相关性，并以此来确定用以恢复误码区域的邻域及其误码块中边缘像素的邻域，再根据人眼视觉,地误码区域的高频与低频部分分别利用不同的策略来先预测，后恢复，并在均方误差最的差错处理能力和良好的差错恢复性能。

In video communication bit-errors, block-errors and macroblock-errors often happen owing to channel noises. They seriously affect video quality and QoS. At the same time retransmission can't match the needs of real-time transmission(RTP) when finding errors. Up to now many methodshave been proposed for error concealment in spatial, temporal, frequent domain and their joint domain. They all tr out to conceal the error with simple algorithm to meet the demand of RTP. In this paper we proposed an error concealment method using the frequent information of error blocks' neighborhood to decide how to conceal the error. It employs Markov random field to describe the relationships between pixels and between blocks. Based on the description we get the neighborhood of pixels and blocks by which to restore the error pixels and error blocks. According to the characters of human vison sstem different methods are used to restore different frequent parts. The high frequent parts, i.e. the deges of image are restored first, then the lower parts. In a least-squear sense linear fitting and multi-directional extrapolation are used to obtain optimal concealment. The experiment results have proved its robust error processing ability and good error concealment performance.