NSCT域多分辨率红外与可见光景象匹配算法  

Multiresolution Scene Matching Algorithm for Infrared and Visible Images Based on Non-subsampled Contourlet Transform

作　　者：刘刚[1] 王光宇[1] 周珩[2] 王明静[2] 

机构地区：[1]河南科技大学信息工程学院,洛阳471023 [2]中国空空导弹研究院,洛阳471009

出　　处：《系统仿真学报》2016年第8期1795-1804,共10页Journal of System Simulation

基　　金：航空科学基金(20130142004);河南科技大学创新能力培育基金(2014ZCX010);河南科技大学博士科研启动基金(0p001631)

摘　　要：针对以可见光图像为基准、红外图像为实测的景象匹配问题,提出一种基于非下采样轮廓波变换(NSCT)的多分辨率匹配方法。利用相位一致性变换削弱红外与可见光图像灰度与对比度差异,对两类图像分别进行非下采样轮廓波变换,引入Krawtchouk矩不变量提取匹配特征,利用克服早熟现象的改进遗传算法作为搜索策略,以两类图像的Krawtchouk不变矩相关系数作为搜索的适应度准则,实现红外目标图像和可见光基准图像的多分辨率匹配。实验结果表明,与常用景象匹配算法相比,本文方法不仅具有更高的匹配精度和速度,而且鲁棒性好,能抵抗实测图像的旋转几何畸变。Aiming at scene matching problem for taking infrared image as the actual data and the visible image as the referenced data, a multiresolution matching algorithm was proposed based on non-subsampled contourlet transform （NSCT）. By using the transform of phase congruency transform, the difference of grayscale and contrast between infrared image and visible light image was weakened. Subsequently, the two types of images were separately transformed into non-subsampled contourlet domain and the proposed method took the Krawtchouk invariant moment as matching feature. The presented method, which used the improved genetic algorithm （GA） as searching strategy which conquered the precocious phenomenon, realized the multiresolution matching between infrared image and visible light image. The presented method used the relative coefficient of Krawtchouk invariant moment between the two types of images as fitness criterion for searching. Experimental results show that the proposed method has not only high matching accuracy and fast matching speed, but also better robustness in comparison with some classic matching algorithms, which can resist the geometric distortion of rotation for actual image.

关 键 词：景象匹配 非下采样轮廓波 相位一致性 Krawtchouk不变矩 遗传算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]