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 薄云污染会影响遥感图像的正常判读和解译。传统去云方法对图像做傅里叶变换,对转为频率域后的图像进行同态高通滤波的整体处理,因而会在去云的同时对无云区域及图像边缘产生较大影响。本文利用小波变换将图像分解为若干频率特征不同的分量,仅仅针对表示薄云的低频近似分量进行同态滤波,最后通过小波重构得到去除薄云的图像。试验结果表明,小波变换使具有高频细节的地物信息免受滤波处理,但连续变化的低频地物信息仍会受到一定影响。

【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 homomor... 更多