一种多波段红外图像联合配准和融合方法

多波段红外图像配准和融合是得到更高质量夜视图像的关键步骤。过去，这两种方法被定义为两个独立的图像处理过程。因此，在融合过程中忽略配准误差会严重影响最后的融合质量。为解决上述问题，该文提出一种新的迭代优化方法，该方法通过寻找最优配准参数来获得最佳的融合性能，采用基于人眼感兴趣区域的清晰度指标作为融合质量评价函数来完善配准过程，采用模拟退火法解决联合优化问题。实验结果表明，针对夜视领域的多波段红外图像，该方法在配准精度、融合质量以及稳定性上明显优于常用的配准和融合算法。

Joint Image Registration and Fusion for Multispectral Infrared Images

The registration and fusion are the two essential steps to get a composed image from the multispectral infrared images in the night vision. However, at present these two processes are considered as two independent steps, where the registration error may significantly affect the fusion quality. In this paper, a novel iteration optimization method is proposed to obtain the optimal registration parameter for the following fusion process. Definition index of the region of interest in the fused image is used to improve the register process, and simulated annealing method is used to solve the joint optimization problem. The experimental results show that the proposed method provides a robust stability and performance over several other state-of-the-art methods in the registration accuracy and fusion quality.