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中文摘要：
针对图像融合中参数优化的问题，提出了一种基于多目标粒子群优化算法的多传感器图像融合方法。首先采用非采样Contourlet变换（NSCT）对源图像进行多尺度、多方向分解；然后选取图像融合的客观评价指标为优化目标函数，采用多目标粒子群优化算法对低频系数的融合参数进行优化，带通方向子带系数采用取绝对值最大的融合规则：最后通过NSCT逆变换得到融合图像。分别对多聚焦图像融合和红外与可见光图像进行融合实验，并对融合图像进行主客观评价，实验结果表明，得到的融合图像具有较好的主观视觉效果和客观评价指标。
英文摘要：
A novel multi-sensor image fusion method based on multi-objective particle swarm optimization is proposed to solve the parameter optimization problem in the image fusion. Firstly, the Nonsubsampled Contourlet Transform （NSCT） is used to perform multi-scale and multi-directional decomposition on the source images. Then select the objective evaluation criteria as the optimal objective function. Multi-objective particle swarm optimization algorithm is used to optimize the fusion parameters of low-frequency coefficients. For band-pass directional sub-band coefficients selection, the rule of maximum absolute value is used. Finally, the fused image is obtained through inverse transform. The algorithm has been used to merge multi-focus images and infrared and visible light images. The experimental results indicate that the fused image obtained by the proposed method has a better subjective visual effect and objective evaluation criteria .
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