针对观测域和像素域两阶段多假设预测重构方案在低采样率时重构效果不理想，且对于运动剧烈的序列预测精度不够、时间复杂度较高等问题，在两阶段多假设预测
的基础上，提出了基于快速搜索的迭代多假设预测重构算法． 该算法利用像素域分块的灵活性，基于重叠块在像素域迭代预测重构; 针对运动较快的序列，采用十字形联合区域搜索方法以减小大范围搜索的算法复杂度; 同时利用图像空间相关性进行帧间/帧内自适应假设块的模式选择与已有算法相比，文中重构算法进一步削弱了块效应，降低了大范围搜索的运算复杂度，提高了重构性能．

As the two-stage multi-hypothesis reconstruction ( 2sMHR) for the prediction in both measurement and pixel domains is of low reconstruction quality at low subrate as well as low prediction accuracy and high computa- tional complexity for fast movement sequences,on the basis of 2sMHR scheme,a novel iterative multi-hypothesis ( IMH) prediction reconstruction algorithm utilizing fast searching technology is proposed.This algorithm utilizes the flexibility of block partition in pixel domain to conduct overlapping block-based iterative multi-hypothesis pre- diction,and adopts the scheme of jointing cross-shaped and regional searching to lessen matching complexity in large-range searching for fast sequences.In addition,by utilizing the space correlation in images,an adaptive in- terframe/intraframe hypothesis-block selecting scheme is presented.In comparison with the existing algorithms,the proposed IMH prediction reconstruction algorithm suppresses the prediction block effect,reduces the computational complexity for large-range searching and improves the video reconstruction quality.