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研究遥感图像融合性能的客观评价问题,分析当前遥感图像融合效果评估方法特点的基础上,提出一种新的遥感图像融合效果评估方法——基于奇异值分解(SVD,Singular Value Decomposition)的方法.利用源图像与融合结果图像的奇异值差异,测量它们之间能量信息失真情况,从而进行融合算法的评估.仿真实验从两方面入手,当融合源图像中含有SAR(Synthetic Aperlure Radar)图像时,对比Piella和Xydeas评估方法较为有效;另一方面,对多类型传感器、不同方法的像素级融合结果进行评估,与主观评价结果对比具有较高的一致性.这种客观评估方法能够较好地反映多类遥感图像融合的质量,是一种实现简单、高效、较为通用的遥感图像融合效果评估方法.
Based on the objective evaluation of remote sensing image fusion performance and the characteristics of current remote sensing image fusion evaluation methods, this paper proposes a new method of remote sensing image fusion evaluation - Singular Value Decomposition (SVD). Using the difference of singular values between the source image and the fused image, the energy information distortion between them is measured and the fusion algorithm is evaluated.From two aspects, the simulation experiment starts from two aspects: when the fused source image contains the SAR image (Synthetic Aperlure Radar) Compared with Piella and Xydeas, the evaluation method is more effective. On the other hand, the evaluation of pixel-level fusion results of different types of sensors and different methods is more consistent with the subjective evaluation results, which can better reflect The quality of multi-types of remote sensing image fusion is a simple, efficient and universal method for evaluating the fusion effect of remote sensing images.