中文摘要：

目的图像变形算法中特征基元提取和匹配方式大部分都是采用人机交互的方式进行,并且在遮挡区域变形时出现较多的鬼影和模糊现象,使得针对同一场景图像变形实现繁琐且效果不佳,针对这些问题提出一种基于多特征融合的自动图像变形算法。方法该算法提取多种图像特征信息（如Surf特征算子、Harris算子、Canny算子等）并进行多特征融合匹配,得到一个分布适当且对应关系正确的三角网格,再结合图像变形,实现自动图像插值。结果实验结果显示,自动的提取特征基元有效地减少了人工操作,而多特征融合匹配有效地抑制了图像变形时边缘或遮挡区域鬼影的产生。结论提出的融合匹配方法,将不同的特征信息有效地融合匹配从而改善了图像变形算法。通过对多组实验结果进行问卷调查,91%的参与者认为该算法有效地改进图像变形结果。

英文摘要：

Objective Image morphing algorithm is a branch of image-based rendering（ IBR）. Normally,it extracts features and matches features by human-computer interaction. However,there are problems in such human-computer interaction algorithms. When occlusion areas are processed,ghosting and blurring have a great chance to occur which are fatal to image morphing algorithms. All these phenomena lead to poor experimental results in the same scene. The implementations of old-fashioned image morphing algorithms are always complicated and inefficient and usually not suitable for practical application. In order to solve these problems,we propose a novel and efficient image morphing algorithm based on multi-feature fusion in this paper. Method In spite of marking two relevant images on edges,corners,and rich-texture areas by human-computer interaction,our proposal innovatively extracts multiple-image feature information（ such as Surf feature,Harris feature,and Canny feature） with multi-feature fusion matching,which obtains a properly distributed triangle mesh pair with correct correspondence. Then,automatic image interpolation is achieved by the conjunction of triangle mesh and image morphing. We select Surf feature,Harris feature,and Canny feature as basic features. First,we extract these image features from the original image and destination image. Then,we process Surf feature based on Delaunay triangulation to obtain an initial triangle mesh. It is fusion matched with Harris features or other image features. According to this step,an accurate and uniform triangle mesh is acquired. We also define a matching cost function,a feature point of color intensity cost,and a grade matching cost to optimize the matching of features. It improves the accuracy of image feature matching. Finally,the image is transformed based on the acquired triangle mesh to a virtual view image between the original image and destination image. Result In the conventional image morphing algorithm,the system will take a long time to choose feature poin