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灰度遥感图像去云技术及其质量的分析

Analysis of quality of removing cloud for monochromatic remote sensing images

  • 摘要: 为了尽可能地呈现灰度遥感图像的信息,对灰图遥感图像分别用小波变换法、改进型多尺度Retinex算法、同态滤波法进行了图像增强处理,分别采用亮度、对比度、亮度与对比度乘积、图像信息熵和变换后的图像与原始图像相比较的保真度等指标对增强后的图像进行分析。结果表明,以采用多尺度Retinex算法增强后,在亮度平均值附近1倍标准差截断、拉伸后得到的图像亮度、对比度、亮度与对比度乘积最高,图像质量最好;小波变换后得到的图像对比度和信息熵最高,去云效果较好;取参量n=1的同态滤波法增强后得到的图像其保真度最高,与原图像最接近,去云效果一般;改进型多尺度Retinex算法和小波变换分别对乌云和白云去除效果最佳。

     

    Abstract: In order to show the best information of monochromatic remote sensing images,it was processed with the algorithms of wavelet transform,advanced mufti-scale Retinex,and homomorphic filter respectively.The criterions of brightness,contrast degree,production of brightness multiplying with contrast degree,information entropy,fidelity were applied to evaluate the quality for the images enhanced by 7 methods and original images.The results showed 3 points.Firstly,the values of brightness,contrast,and production of brightness multiplying with contrast were largest and their image quality was best when the images handled by mufti-scale Retinex and stretched the range of k=1 time standard deviation near the mean brightness.Secondly,the values of contrast and information entropy were biggest and their image quality was well when the images handled by wavelet transform with a high-pass filter.Finally,the value of fidelity was largest in all algorithms and their image quality was common when the images handled by homomorphic filter with n=1.The algorithms of advanced mufti-scale Retinex and wavelet transform were best for removing black cloud and white cloud in remote sensing images respectively.

     

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