A sift-based method for image mosaic

Meiqun Jiang, Jingxin Hong, Q. Liao, Shengluan Huang
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引用次数: 4

Abstract

This paper proposes a mosaic algorithm based on SIFT(Scale Invariant Feature Trasform). Keypoints and their descriptors are exacted by SIFT, which ensures the algorithm robust to translation, rotation, noise and scalling. Then proposed matching algorithm is used to match the keypoints. First, rough match pairs are obtained by Nearest Neighbor algorithm. Second, match rate information of the neighbor keypoints and the global information are calculated to update the match precision, so each keypoint matching rate spreads to its neighborhood, which eliminates a large number of mismatches to achieve the exact match. Third, RANSAC is applied to obtain the transformation matrix. Finally, two images are stitched by linear weighted fusion algorithm. The experiment results confirm the feasibility and improvement of our model.
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一种基于筛选的图像拼接方法
提出了一种基于SIFT(Scale Invariant Feature transform)的拼接算法。通过SIFT提取关键点及其描述符,保证了算法对平移、旋转、噪声和调用的鲁棒性。然后用提出的匹配算法对关键点进行匹配。首先,采用最近邻算法获得粗糙匹配对;其次,计算相邻关键点的匹配率信息和全局信息,更新匹配精度,使每个关键点的匹配率向其邻域扩散,消除大量不匹配,实现精确匹配;第三,利用RANSAC算法得到变换矩阵。最后,采用线性加权融合算法对两幅图像进行拼接。实验结果证实了该模型的可行性和改进性。
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