基于矩阵二阶矩和小波分解的紊流图像融合灰色关联度评价

Evaluation of Gray Relational Degree of Turbulence Image Fusing Based on Matrix Quadratic Moment and Wavelet Decomposition

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.