基于智能优化算法的异源激光图像匹配研究

Research on matching of heterogeneous laser images based on intelligent optimization algorithm

针对当前异源激光图像匹配方法不能去除异源激光图像中噪声,匹配时间长、匹配结果与实际结果之间的误差大等问题,提出基于智能优化算法的异源激光图像匹配方法。首先对异源激光图像进行变换分解,利用高斯模型和双边滤波去除噪声信号,然后提取去噪处理后异源激光图像中的直线描述符,并进行归一化处理,根据处理得到的结果提取异源激光图像的匹配点,构建异源激光图像的匹配点集合,最后引入智能优化算法去除匹配点集合中存在的误匹配点,根据匹配点的像素灰度值差异和权值果构建异源激光图像匹配模型,实现异源激光图像的匹配。实验结果表明,本文异源激光图像匹配方法的去噪性能好、匹配效率高、匹配结果准确率高,具有比较明显的优越性。

Aiming at the problem that the current heterologous laser image matching methods can not remove the medium noise in heterologous laser images,the matching time is long,and the error between the matching results and the actual results is large,an intelligent optimization algorithm based heterologous laser image matching method is proposed.Firstly,the heterologous laser image is transformed and decomposed,then the Gaussian model and bilateral filtering are used to remove the noise signal.Then the linear descriptors in the denoised heterologous laser image are extracted and normalized.The matching points of the heterologous laser image are extracted from the processed results,and the matching of the heterologous laser image is constructed.Finally,an intelligent optimization algorithm is introduced to remove the mismatching points in the matching point set.According to the difference of pixel gray value and the weight result of the matching points,a matching model of heterologous laser images is constructed to realize the matching of heterologous laser images.Experimental results show that the proposed method has good denoising performance,high matching efficiency,high matching accuracy and obvious advantages.