基于特征点和泊松融合的红外序列图像拼接

提出了一种基于特征点和重叠过渡泊松融合的红外序列图像无缝拼接方法。该方法首先采用简化的SIFT特征提取方法获得图像特征点，然后利用双向互匹配的方法提高特征点的匹配精确度，再通过引入随机抽样一致性（RANSAC）算法剔除误匹配点对并求出图像间的变换矩阵，最后将改进的重叠过渡的泊松融合完成图像间的无缝拼接。该算法具有很好的鲁棒性，允许图像有旋转变换和缩放变换，且不受图像噪声影响。实验结果表明:该方法简单有效，可以在保持图像清晰度的前提下，明显消除拼接缝隙，提高拼接图像的质量。

Infrared image sequence mosaic based on feature points and Poisson fusion

A seamless IR image sequence mosaic method based on feature points and principle of overlap transition Poisson image fusion was proposed. Firstly, a simplified SIFT was used to extract invariant feature points from images. In order to improve the accuracy of matching, bidirectional and complementary matching method was used. Then, random sample consensus(RANSAC) was used to perform reliable matching parameters of the transformation between images which were obtained from the matched feature points. Finally, Poisson image fusion was used to accomplish seamless image mosaic. The feature points were invariant to affine transformation, noise contamination, leading to robustness of the method. Experimental results show that the image mosaic method is simple and effective, and eliminate the mosaic seams while keeping good image definition.