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An algorithm of remote sensing image fusion based on nonsubsampled contourlet transform

机译:一种基于非基于非管制型轮廓变换的遥感图像融合算法

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This paper presents a remote sensing image fusion method based on multiresolution analysis (MRA). The lower spatial resolution multispectral (MS) images are sharpened by injecting high frequency components which are extracted from higher spatial resolution panchromatic (Pan) images by using nonsubsampled contourlet transform (NSCT). In order to improve the visual quality of fusion images, this paper proposes a fusion rule based on human visual characteristics. Experiments are carried out on images acquired by the SPOT-5 satellite system. Firstly, MS images are resampled to finer scale as same as Pan images and are converted from RGB format to HSV format. Secondly, the value (V) band of HSV format MS image is sharpened by the Pan image by means of NSCT. Finally, fusion quality assessments among the proposed method and other commonly used remote sensing image fusion methods reveal that both the visual and parametric quality of the proposed method are better than other methods.
机译:本文提出了一种基于多分辨率分析(MRA)的遥感图像融合方法。 通过使用非空间分辨率的Contourlet变换(NSCT)来注入从较高空间分辨率(PAN)图像中提取的高频分量来锐化较低的空间分辨率MultiSpectral(MS)图像。 为了提高融合图像的视觉质量,本文提出了一种基于人类视觉特征的融合规则。 实验在点5卫星系统获取的图像上进行。 首先,MS图像重新采样以更精细地与PAN图像相同,并且从RGB格式转换为HSV格式。 其次,通过NSCT通过PAN图像锐化HSV格式MS图像的值(V)频带。 最后,融合质量评估在提出的方法和其他常用的遥感图像融合方法中揭示了所提出的方法的视觉和参数质量优于其他方法。

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