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中文摘要：
基于人类视觉系统和源图像特性，该文提出一种非下采样Contourlet域图像融合算法，并讨论了分解层数和方向分解数对融合结果的影响。低通子带引入闭环反馈策略自适应获取近似最优融合权值；高通子带则基于区域能量定义像素活性测度，以有效增强图像的对比度，并保持细节信息。实验结果表明：该文提出的图像融合新算法具有较好的鲁棒性，融合图像边缘的清晰度和连续性也较理想。
英文摘要：
An image fusion algorithm in nonsubsampled Contourlet domain is presented based on Human Visual System （HVS） and source image characteristics. Moreover, the influence on fusion result of decomposition levels and directional decomposition numbers is discussed. Closed Loop Feedback （CLF） is introduced into low-pass subbands to obtain optimal fused weights adaptively. In high-pass subbands, Activity Measure （AM） is defined based on region energy to enhance contrast of fused images and protect detail information of source images. Experiment results show that the proposed fusion technique is robust and the fusion images have ideal clear and continue edges.
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