基于特征点匹配对平面相似度的图像拼接

针对来自于不同视点拍摄的具有视差的两幅图像，提出了一种基于特征点匹配对平面相似性的图像拼接方法。该方法利用场景中属于同一平面特征点之间的变换矩阵一致性的特点，通过定义特征点匹配对之间的平面相似度来筛选特征点匹配对，有效降低了特征点的漏匹配率，提高了配准精度。采用图割算法计算图像的最优缝合线，进行拼接得到最终结果。实验结果表明，与现有经典算法相比，该方法具有较好的视差鲁棒性。

Image Stitching Based on the Planar Similarity Among Matching Pairs of Feature Points

An image stitching method for two images with parallax taking at different viewpoints is proposed based on the planar similarity among matching pairs of feature points. This method makes use of the property that feature points belonging to the same plane often share the same transformation matrix. By defining the planar similarity measure between feature point pairs, the missed matching rate is effectively decreased, and the image registration accuracy is improved. Subsequently, we adopt a graph cut-based algorithm to obtain the optimal stitching line. Experimental results on several datasets have demonstrated that our method outperforms the current state-of-art methods with a better anti-parallax robustness.