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- W2372634320 abstract "Thin cloud is considered annoying contamination on remote sensing imagery,as it can seriously affect the image analysis.Cloud removal is commonly performed with a homomorphic filter(e.g.the butter worth or exponential filter) applied to the fourier transformed frequency image.One drawback of the method is that it is unable to separate the low-frequency component from the high frequency in the filtering process,thus leading to information loss in the non-cloud region.This paper presents a homomorphic filtering based on wavelet transformation for cloud removal,which can avoid the above drawback.This procedure decomposes an image into low-frequency and high-frequency components,and then employs a high-pass filter to process the low-frequency(cloud) component.The filtered image is finally recovered from all the other components with this processed one through wavelet reconstruction.Test evaluations indicated that the filtered image resulting from the wavelet-based approach performed better than the image from the conventional fourier transformation in terms of changes in the mean,standard deviation,and entropy of image brightness values." @default.
- W2372634320 created "2016-06-24" @default.
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- W2372634320 date "2011-01-01" @default.
- W2372634320 modified "2023-09-26" @default.
- W2372634320 title "Wavelet-based Cloud Removal from High-resolution Remote Sensing Data:An Experiment with QuickBird Imagery" @default.
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