Automatic radiometric normalization with genetic algorithms and a Kriging model

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8 引文 斯高帕斯(Scopus)


An automatic procedure of radiometric normalization is proposed for multi-temporal satellite image correction, with a modified genetic algorithm (GA) regression method and a spatially variant normalization model using the Kriging interpolation. The proposed procedure was tested on a synthetic altered image and an image pair from FORMOSAT-2; the results show that the GA method is more robust than the conventional PCA methods in high-resolution imaging, and that different regression-error evaluation models have different sensitivities to the linear regression parameters. A statistical comparison demonstrates that 1-km sampling spacing is able to successfully achieve the parameter spatial variation. Error validation on FORMOSAT-2 image pair shows it is a decent combination of radiometric normalization with GA estimation and a spatially variant parameter normalization model.

頁(從 - 到)42-51
期刊Computers and Geosciences
出版狀態Published - 2012 6月

All Science Journal Classification (ASJC) codes

  • 資訊系統
  • 地球科學電腦


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