线性正则化遥感反演中正则化参数的确定方法

A Regularization Parameter Choice Method on Linear Quantitative Remote Sensing Inversion

  • 摘要: 研究了线性正则化反演中正则化参数的确定方法,提出了以香农熵减最大化为条件的正则化参数确定方法——最大熵法,并以具体遥感反演实例,和常规正则化参数确定方法比较,证明了最大熵法在观测数据误差不大的情况下有明显优势,在观测数据误差方差大、而先验知识精度较高时也显示优势。

     

    Abstract: Choosing a regularization parameter in linear quantitative remote sensing inversion is studied.From the point of information theory,a new regularization parameter choice method called maximum entropy method is proposed.Compared with other methods,the new method shows its obvious advantage in the case of that the error of the observations used in inversion process is not large or the prior knowledge has a higher precision.

     

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