中文摘要：

视频帧纹理区域舍有的大量周期重复模式常导致双向运动估计发生视频块的错匹配，从而导致帧率提升算法重建的内插视频质量衰退。为了克服该问题，提出提取视频帧的多个特征加入到块匹配中，以降低错匹配发生的可能性。由于视频天然具有彩色信息，因此色差分量首先被加入到块匹配中。另外，人眼对图像边缘较敏感．因此．由简单的Sobel算子计算出的梯度被使用去反应边缘特征并融入至块匹配多特征匹配尽管可有效地提高运动估计精度，但也引入了较高的计算复杂度。为了减少计算复杂度，一个特殊模板被设计去将多特征合并到单平面上，那么，只需进行一次块匹配运算就可完成多特征的匹配，在节省计算复杂度的同时也提高了运动估计精度。仿真实验表明，该算法以较低的计算复杂度获得了良好的内插帧主客观质量。

英文摘要：

It usually results in the quality degradation of the interpolated frame in frame rate up-conversinn that lots of periodical repetitive patterns in the texture region of video frame lead to the mismatch of video blocks for bidirectional motion estimation. To overcome this problem, this paper proposes to extract multiple features of video frame and add them into the process of block-matching,and thus the probability of appearing mismatch is lowered. Since the video sequence naturally contains color information,the chrominance component is firstly mixed into the block-matching. Besides,human~ eyes is obviously sensitive to image edges, and therefore the gradient component,which is computed by the simple Sobel operator,is used to reveal the edge feature and mixed into the bloek-matehing. Ahhough the multiple features matching can effectively improve the aceuracy of motion estimation,it introduces also the higher computational complexity. To reduce the computational complexity of multiple fealnres matching, a special template is designed to combine muhiple features into a single panel ,thereby completing multiple features matching by performing only a block-matching operation, which improve the acenraey of motion estimation while guaranteeing a low computational complexily. Experimental results show that the proposed algorithm can improve the both subjective and objective quality of the interpolated frame with a low cnmpntational complexity.