基于经验模态分解的图像拼接

Image Stitching Based on Empirical Mode Decomposition

对待拼接图像分别进行经验模态分解,对分解得到的第一个固有模态函数与第二个固有模态函数的叠加进行特征点提取、特征点匹配与变换矩阵的估计以实现图像的拼接,文中提出的方法有效提高了特征点匹配的正确率,具有很强的鲁棒性。在图像融合方面文中提出一种新的基于余弦关系变换的加权融合技术,在实现图像无缝拼接的同时,可有效去除拼接图像重叠区域的重影与鬼影现象。

The first two intrinsic mode functions of each image are obtained by using empirical mode decomposition algorithm to decompose images which need stitch.Through this method,the feature points are extracted and matched from the first two intrinsic mode function’s superimposition of each image.Based on these matched feature points pairs,parameters of the transformation matrix are calculated and then images are stitched.Experimental results have shown that this method effectively improves the accuracy rate of the feature points matched and has strong robustness.On image fusion,a novel weighed technique based on cosine relationship transform is proposed.With this technique,not only the seamless stitching images can be obtained,but also the phenomenon of ghosting in the overlapping stitching region can be eliminated.