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- W2379966642 abstract "There are sometimes some uneven thin cloud-fog effects in the remote sensing images from optical remote sensors,especially in cloudy and rainy areas.A new method based on adaptive filtering and gray-scale transformation was proposed to remove the cloud-fog cover of the high-resolution remote sensing images in this paper.This comprehensive technology program was applied to process the SPOT5 image with heavy thin cloud-fog cover acquired from Zhuhai,China.And to test its superiority,a comparative experiment with two other available methods named homomorphism filter and an approach based on Laplacian enhancement and histogram transformation was carried on.Several objective indicators,such as PSNR(Peak Signal-to Noise Ratio),average absolute deviation and spectral correlation coefficient(proposed by Li Yuechen[1]),were used to evaluate the resulting images.Besides,to verify the general reliability of the framework proposed,more image data from different sensors,such as TM and CMB satellite,in the cloudy and rainy areas were selected for the corresponding experiment.The results indicate that the experimental results for different data source are consistent,which show that the proposed integrated methods can remove the thin cloud-fog cover effectively and maintain the true spectral features of the original image to a large extent.Furthermore,as a result of the application of different parameters of filtering and gray-scale transformation for different spectral band,the spatial details and true spectral information are remained as more as possible." @default.
- W2379966642 created "2016-06-24" @default.
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- W2379966642 date "2009-01-01" @default.
- W2379966642 modified "2023-09-24" @default.
- W2379966642 title "Thin Cloud Cover Removed from High-Resolution Remote Sensing Images Based on the Adaptive Filtering and Gray-scale Transformation" @default.
- W2379966642 hasPublicationYear "2009" @default.
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