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摘要: 给出了一种新的基于小波多尺度分解的分层图像融合方法.其基本思想是先对源图像 进行小波多尺度分解;其次,按照融合规则,采用基于区域特性量测的选择及加权算子去构造融 合图像对应的小波系数;最后,通过逆小波变换重构融合图像.该方法被成功地用于图像的融合 处理.此外,利用熵、交叉熵、互信息、均方根误差、峰值信噪比等参量,对该融合方法的融合性能 进行了评价与分析.实验结果表明,该融合方法是十分有效的.Abstract: A novel hierarchical image fusion scheme based on wavelet multiscale decomposition is presented. The basic idea is to perform a wavelet multiscale decomposition of each source image first, then the wavelet coefficients of the fused image are constructed using region-based selection and weighted operators according to different fusion rules, finally the fused image is obtained by taking inverse wavelet transform. This approach has been successfully used in image fusion. In addition, with the use of the parameters such as entropy, cross entropy, mutual information, root mean square error, peak-to-peak signal-to-noise ratio, the performance of the fusion scheme is evaluated and analyzed. The experimental results show that the fusion scheme is effective.
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Key words:
- Image fusion /
- multisensor fusion /
- wavelet decomposition /
- image processing
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