摘要
针对遥感影像中阴影的存在直接影响影像质量以及地物信息提取和识别,而现有的阴影补偿方法在普适性上都有一定的局限性问题,该文结合Curvelet变换理论,对常用的基于HIS色彩空间的阴影补偿算法进行改造,提出了一种Curvelet变换和HIS色彩模型相结合的高分辨率遥感影像阴影补偿新算法:首先对遥感影像进行色彩空间变换,将影像从RGB空间转换到HIS空间,对人眼非常敏感,且包含丰富纹理信息的I分量进行曲波变换;然后对变换的高频和低频系数进行补偿处理,同时依据阴影区域及其周边非阴影区域的均值和标准差分别对H和S分量进行修正处理;最后将处理后的H、I和S分量进行色彩空间逆变换。实验结果表明,与同态滤波、单一HIS色彩模型、小波变换和HIS色彩模型相结合等常用的阴影补偿算法相比,Curvelet变换和HIS色彩模型相结合的算法能够取得更好的补偿效果。
The shadow in remote sensing image means poor image quality,which increases the difficulty in extracting and recognizing the object information from images,but the common methods used in compensating shadow have some limitations.In this paper,a new shadow compensation algorithm based on curvelet transform and HIS color model is proposed for high resolution remote sensing images.This algorithmcontains following steps:Firstly,convert images from RGB space to HIS space;and then,‘I'component is played curvelet transform into HIS space,which is very sensitive to human eyes and contains abundant texture information;Secondly,compensate the high frequency and low frequency coefficients from curvelet transform,adjust‘H'and ‘S'components according to the average value and standard deviation of shadow region and its adjacent non-shadow region;Finally,I,H and Scomponents after compensated are performed color space inverse transformation.Experimental results show that,compared with common algorithms,such as homomorphic filtering algorithm,separate HIS color model,wavelet transform and HIS color model,the new algorithm could achieve better shadow compensation effect.
引文
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