基于改进IGG模型的全景图像拼接缝消除算法

为了提高序列图像拼接得到的全景图的质量,通常将L-M(Levenberg-Marquardt)算法用于图像拼接中变换模型的参数优化,但L-M算法不能消除误匹配点对模型求解的影响。为了消除误匹配点的影响,提出了基于IGG(Institute of Geodesy & Geophysics)函数模型的抗差L-M算法。首先利用IGG算法的迭代过程具有良好的抗粗差能力和可靠的收敛性等特点来优化变换模型,提高图像配准的精准度。然后采用自适应区域的拉普拉斯多分辨和最优拼接缝相结合的方法对拼接结果进行融合,以消除因拼接缝及光照不均而造成的过渡不连续现象。实验结果表明,所提算法不仅有效提高了配准精度,同时还实现了无缝拼接,获得了高质量的无缝拼接全景图。

Algorithm of Eliminating Image Stitching Line Based on Improved IGG Model

In order to improve the quality of panorama obtained by image stitching,L-M(Levenberg-Marquardt) algorithm is usually applied to the parameter optimization for image mosaic of the transform model,but it cannot eliminate the influence of mismatching points of the model solution.To solve this problem,robust L-M algorithm based on IGG function model was proposed.Firstly,the iterative process of IGG algorithm has the characteristics of strong resistance to gross error and high convergence speed,which contribute to optimize transformation model and improve the accuracy of image registration.Secondly,the method of combining Laplacian multi-resolution fusion algorithm of the adaptive region and the optimal stitching line is used to eliminate transition discontinuity,which is caused by the seam and uneven illumination.The experimental results show that the improvesd algorithm not only effectively improves the registration accuracy,but also achieves a seamless and high quality panorama.