基于Contourlet变换的多传感器图像融合

A Multi-sensor Image Fusion Method Based on Contourlet Transform

单一传感器无法完全描述图像完整信息,但多传感器可以获得更多的图像信息。针对目前图像融合方法存在边缘模糊、重要信息丢失等不足,提出一种基于Contourlet变换的多传感器图像融合方法。采用Contourlet变换对采集的图像进行多尺度、多方向分解;然后采用不同规则分别对低频子带系数和高频子带系数进行融合;最后采用Contourlet逆变换对各子带信号进行重构得到融合后图像。实验结果表明,本方法的融合后图像过渡效果自然,提高了图像质量,而且性能优于其它图像融合方法。

Single sensor can not fully describe image information, and multi-sensor image fusion can get more image information. Aiming at the edge fuzzy, important information loss and other issues in image fusion methods, a muhi-sensor image fusion meth- od based on Contourlet transform is put forward. Firstly, the paper uses Contourlet transform decomposes the acquired image in multi-scale and muhi-orientation, then use different rules respectively to fuse the low-pass and high-pass sub, and finally the fused image is reconstructed by using inverse Contourlet transform. The results show that image of the proposed method is more natural, and image quality and fusion result are better than other image fusion methods.