为了实现苹果树冠层的三维重建，指导智能剪枝、疏花和采摘，构建了集成光学混合探测(PMD)摄像机和彩色摄像头的图像采集系统，研究了不同生长时期的多源图像配准方法。从相似度评价指标和PMD图像的像素可靠性两个方面来描述果树不同生长时期图像的不同特征。结合图像的特征信息，提出了应采用基于深度信息的多源传感器标定技术，实现果树从开花期到成熟期的图像配准；对休眠期到发芽期的果树图像应采用基于图像特征的多源图像配准算法。对自然场景下的成熟期、休眠期、开花期果树图像共90组进行图像特征分析和不同配准方法试验验证，成熟期和开花期的匹配率达到100%，休眠期的匹配率达到86.11%。

In order to realize three-dimensional (3D) reconstruction for canopy and guide the operations of intelligent pruning, flower thinning and picking, a multi-image registration algorithm of apple tree at different growth stages is restigated. The robot vision system includes a color camera system and a photo mixing detector (PMD) camera. Image features at different growth stages are described by image similarity and reliable pixels. According to these image features. The optical calibration based on the distance information can be used from the flowering to the mature stage, while from the dormancy to the germination stage, the multi-image registration algorism should be used. Ninety groups of pictures, including the stages of mature, dormancy and flowering are used to verification the viewpoint. The experimental result shows that, the matching rate reaches 100% at mature stage and flowering stage, while 86.11% at dormancy stage.