不同融合算法从不同角度对融合图像产生解释，从而产生不同亮度、不同对比度的融合图像。对融合算法进行性能分析可减少图像信息的不确定性，提高图像解析度。在总结现有图像融合算法基础上，对不同融合算法获得的融合图像，采用主观评价方法进行打分排序。实验结果表明，相比加权融合算法，塔型融合算法和小波变换融合算法具有更好的场景适应性，有利于提高场景中的重要特征和图像细节。加权融合算法虽然对特定场景会获得较高分值，但在场景适应性上存在一定局限性。因此，对于实际应用的图像融合系统应根据不同的任务要求和应用环境，选择采用不同的融合算法，以期达到最佳的场景解释效果。

Different fusion algorithms interpret fusion images from different aspects, which generate fusion images of different brightnesses and different contrasts. Image fusion algorithms performance analysis can reduce the uncertainty of image information and improve the image resolution. Based on the generalization of these existing fusion algorithms, these fusion images obtained by different fusion algorithms are collated by means of subjective assessment score. The experimental result indicates the pyramidal fusion algorithms and wavelet transform algorithms can improve the important characteristics and image detail, which have better adaptability than those of weighted fusion algorithms in different scene. Though weighted fusion algorithms can get higher score in special scene, it has limitation of scene adaptability. Therefore, the practical image fusion system should choose different fusion algorithms to adjust different task requirements and applied circumstances in order to acquire the optimum scene interpreting effect.