Aiming at the complex computation and time-consuming problem during unordered image stitching, we present a method based on the binary tree and the estimated overlapping areas to stitch images without order in this paper. For image registration, the overlapping areas between input images are estimated, so that the extraction and matching of feature points are only performed in these areas. For image stitching, we build a model of the binary tree to stitch each two matched images without sorting. Compared to traditional methods, our method significantly reduces the computational time of matching irrelevant image pairs and improves the efficiency of image registration and stitching. Moreover, the stitching model of the binary tree proposed in this paper further reduces the distortion of the panorama. Experimental results show that the number of extracted feature points in the estimated overlapping area is approximately 0.3~0.6 times of that in the entire image by using the same method, which greatly reduces the computational time of feature extraction and matching. Compared to the exhaustive image matching method, our approach only takes about 1/3 of the time to find all matching images.

中文翻译：

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一种基于二叉树和估计重叠区域的无序图像拼接方法。


针对无序图像拼接过程中计算复杂、耗时的问题，提出一种基于二叉树和重叠区域估计的无序图像拼接方法。对于图像配准，估计输入图像之间的重叠区域，以便仅在这些区域中进行特征点的提取和匹配。对于图像拼接，我们构建了一个二叉树模型来拼接每两个匹配的图像而不进行排序。与传统方法相比，我们的方法显着减少了匹配不相关图像对的计算时间，提高了图像配准和拼接的效率。而且，本文提出的二叉树拼接模型进一步减少了全景图的畸变。实验结果表明，采用相同的方法，估计重叠区域中提取的特征点数量约为整幅图像的0.3~0.6倍，大大减少了特征提取和匹配的计算时间。与穷举图像匹配方法相比，我们的方法只需要大约 1/3 的时间即可找到所有匹配图像。