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A New Approach on Optimization of the Rational Function Model of High-Resolution Satellite Imagery

机译:优化高分辨率卫星影像有理函数模型的新方法

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Overparameterization is one of the major problems that the rational function model (RFM) faces. A new approach of RFM parameter optimization is proposed in this paper. The proposed RFM parameter optimization method can resolve the ill-posed problem by removing all of the unnecessary parameters based on scatter matrix and elimination transformation strategies. The performances of conventional ridge estimation and the proposed method are evaluated with control and check grids generated from Satellites d'observation de la Terre (SPOT-5) high-resolution satellite data. Experimental results show that the precision of the proposed method, with about 35 essential parameters, is 10% to 20% higher than that of the conventional model with all 78 parameters. Moreover, the ill-posed problem is effectively alleviated by the proposed method, and thus, the stability of the estimated parameters is significantly improved.
机译:过度参数化是有理函数模型(RFM)面临的主要问题之一。提出了一种新的RFM参数优化方法。所提出的RFM参数优化方法可以通过基于散布矩阵和消除变换策略消除所有不必要的参数来解决不适定问题。使用从地面卫星观测(SPOT-5)高分辨率卫星数据生成的控制和检查网格,评估了常规脊线估计和所提出方法的性能。实验结果表明,所提出的方法具有约35个基本参数的精度,比具有全部78个参数的常规模型的精度高10%至20%。此外,通过所提出的方法有效地减轻了不适的问题,从而显着提高了估计参数的稳定性。

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