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

机译:基于非下采样轮廓波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:提出了一种基于多分辨率分析(MRA)的遥感图像融合方法。通过注入高频分量,可以降低空间分辨率的多光谱(MS)图像的清晰度,这些高频分量是通过使用非下采样轮廓波变换(NSCT)从较高空间分辨率的全色(Pan)图像中提取的。为了提高融合图像的视觉质量,提出了一种基于人眼视觉特征的融合规则。对SPOT-5卫星系统获取的图像进行了实验。首先,与平移图像一样,将MS图像重新采样到更精细的比例,然后从RGB格式转换为HSV格式。其次,借助于NSCT,通过Pan图像来锐化HSV格式MS图像的值(V)带。最后,对所提方法与其他常用遥感影像融合方法的融合质量评估表明,所提方法的视觉和参数质量均优于其他方法。

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