基于局域方差系数与幅度均值的非线性扩散

在对SAR图像进行处理时,可以将图像分解为代表不同图像特征的多个分量.针对不同分量分别选取最合适的处理方式能够得到性能上的较大提升的问题,使用非线性扩散方法,将图像分解为表征大尺度结构信息的结构分量和表征小尺度细节信息的纹理分量,并对扩散参数的选择进行了对比和评估.提出了一种基于局域方差系数与窗口幅度均值积的扩散参数,作为判断图像中加强或者削弱扩散活动的条件.经过实验证明,采用这种扩散系数能够使得扩散的进行更有针对性,所得到的图像分量能够更加有效地用于后续处理.

Nonlinear diffusion method based on local variance and mean amplitude

With the processing of the synthetic aperture radar(SAR) imaging,the image can be decomposed into different components.Each component corresponds to different properties,which can be processed by a corresponding algorithm in order to get better performance.A nonlinear diffusion method based image decomposing algorithm is proposed,and the image can be decomposed into the structural component and the textural component which represents the large scale smooth features and the small scale texture features respectively.With the diffusion processing,the diffusion parameter is evaluated,and a parameter,which is the product of the local variance and the mean amplitude,is proposed.The proposed parameter can be used as the criterion of enhancing or weakening the diffusion processing.Finally,the testing results indicate that the diffusion processing has better pertinence for the following target recognizing and image compressing.