一种新的ICA域图像融合算法

Novel ICA Domain Multimodal Image Fusion Algorithm

针对红外和可见光图像的特点,结合Mitianoudis提出的ICA域图像融合方法,本文提出了一种改进的ICA域多模图像融合算法。该方法根据Mitianoudis的方法,通过训练得到的基函数对图像进行线性变换,在变换域中将图像分割成不同的区域,对活跃区域采用绝对值取大的融合规则,而对非活跃区域则按照目标传感器图像的区域分割结果分别采取不同的融合规则,最后反变换得到融合图像。实验结果表明了本文方法的有效性。

Aimed at features of infrared and visible images and combined with Mitianoudis＇s fusion method, an improved Independent Component Analysis （ICA） domain multimodal image fusion algorithm was presented. According to Mitianoudis, linear transformation was performed to the source images using ICA bases obtained from offline training. Then the image in ICA domain was segmented into different regions： active regions and non-active regions. For the active region, the ＂max-abs＂ fusion rule was used, while for the non-active region, different fusion rules were used according to the region segmentation result of the target sensor image. Finally, the fused image was reconstructed by the inverse transform. Experiment results demonstrate the effectiveness of the method.