在引入多尺度小波分析的基础上,通过对紊流图像进行多尺度小波分解,建立小波系数矩阵二阶矩以标识对应部分的图像清晰度,通过特定选择机制进行图像重建,最终获得清晰的图像融合结果.选取紊流图像特征建立参数数据组,构建灰色评价数学模型,计算各图像特征之间的灰色关联度,得出了研究结论与参考建议.该实验使紊流图像的细节和缺陷等能够得到很好的展现,为图像融合关联度的监控和调试提供了理论基础和技术准备.%On the basis of introducing the technology of multi-scale wavelet analyze, turbulence images are wavelet decomposed, quadratic moment of corresponding image' s wavelet coefficients is used to identify the definition of image. Thus the required image definition is gotten by wavelet reverse analyzing and reconstructing of image with a specific selecting criteria. After selecting different image characteristics and establishing its parameter-array, a mathematical model of gray evaluating system is structured. After calculating the gray relational degree of the image characteristics, thus the research conclusions and referential suggestions are reached. It provides a clear turbulence image which identifies its detail and defect effectively, the theoretical foundation and technical preparation can be provided for the monitoring and adjusting of image fusion' s relational degree.
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