Hyperspectral Remote Sensing Data Recovery via Adaptive Window Matching Method

نویسندگان

  • Yiliang Zeng
  • Jinhui Lan
  • Chuanzhao Han
  • Libo Jiang
  • Xuefei Shi
چکیده

HJ-1A satellite is often used to monitor environmental disaster and plays an important role in environmental changes. Because of the affection of various factors, certain band of HJ-1A hyperspectral remote sensing data is severe loss or distortion, which brings great difficulties for subsequent quantitative processing. A novel adaptive window matching algorithm, which can adjust intelligently size of matching window according to different local feature information of the image, is proposed for HJ-1A satellite hyperspectral data recovery in this paper. The results show that the adaptive matching algorithm has a more superior performance than other algorithms in image quality index, column mean curve, and image correlation coefficient.

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عنوان ژورنال:
  • iJOE

دوره 11  شماره 

صفحات  -

تاریخ انتشار 2015