中文摘要：

三维图像拼接是通过锥束CT(CBCT)获取大尺寸物体完整的高分辨率三维图像过程中的关键技术之一,成为目前三维图像处理的一个新的研究方向.针对基于特征点的三维CBCT图像拼接技术中相似特征匹配正确率低、匹配过程耗时长的问题,提出一种基于全局二值特征描述子的三维CBCT图像快速匹配算法.首先对二值特征描述子BRIEF进行三维拓展,以适应三维图像;在此基础上加入全局描述子,增强特征描述子的独特性;在特征点匹配时,根据上述特征描述子的特点设计由粗到精的匹配策略,提高特征匹配正确率和效率.实验结果表明,该算法简单有效,可以在大量相似特征条件下提高特征点匹配的正确率,同时也显著提升了匹配速度.

英文摘要：

3D image mosaic is a crucial technology to obtain the whole high-resolution image of large-size object by cone beam computed tomography (CBCT) system, which has become a new research direction of 3D image processing. Aiming at the low matching accuracy of similar features and the time-consuming of feature matching process, we propose a fast feature matching algorithm based on global binary descriptor. The method firstly ex-tends the original BRIEF (Binary robust independent elementary features descriptor) to the 3D case to suit 3D images. Then a global binary descriptor is added to it to enhance the discrimination of the 3D extended feature descriptor. Finally, according to the characteristics of feature descriptor mentioned above, a coarse-to-fine feature matching strategy is designed to improve the accuracy and efficiency of feature matching. Experiments show that the proposed method is simple and effective, which can bring down the number of mismatches and improve the matching speed obviously.