A Regularization Parameter Choice Method on Nonlinear Ill-posed Quantitative Remote Sensing Inversion

Regularization parameter is a key parameter in nonlinear ill-posed quantitative remote sensing inversion.Taking land surface and atmosphere parameters retrieval for example,and taking Shannon entropy reduce as a quantity to express information utilization in retrieving process,a quantitative method is deduced on reasonable hypothesis.The new method is on choosing regularization parameter(prior information ratio) in iteration process of nonlinear ill-posed quantitative remote sensing inversion.On the condition of the stability of inversion,the new method takes good advantage of information of observations.The result reveals that the precision of the object parameter is improved.