| 基于参考波段的去除HJ-1A星HSI图像中条带噪声的方法 |
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| 引用本文： | 高海亮,顾行发,余 涛,赫华颖,王 峰,祝令亚.基于参考波段的去除HJ-1A星HSI图像中条带噪声的方法[J].红外,2013,34(3):7-11. |
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| 作者姓名： | 高海亮 顾行发 余 涛 赫华颖 王 峰 祝令亚 |
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| 作者单位： | 1. 中国科学院遥感应用研究所遥感科学国家重点实验室,北京,100101
2. 中国资源卫星应用中心,北京,100094 |
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| 基金项目： | “十二五”民用航天技术预先研究项目； 国家自然科学基金(41201344)；中国科学院遥感应用研究所知识创新工程青年人才领域前沿项目(Y1S01800CX) |
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| 摘 要： | 环境卫星HJ-1A搭载的超光谱成像仪自2008年9月发射以来,已获取了大量影像数据.由于超光谱成像仪部分波段的图像存在明显的条带噪声,其图像应用效果受到严重影响.本文针对该图像噪声的特点,提出了一种基于参考波段的移动窗口条带噪声去除方法.结果表明,新的噪声去除算法不仅可以有效去除图像的条带噪声,显著提高图像的清晰度,而且还保留了原始图像的基本信息.该方法具有处理速度快、适用性广等优点,是一种理想的条带噪声去除方法.
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| 关 键 词： | 条带噪声去除 高光谱遥感 参考波段 超光谱成像仪 |
| 收稿时间： | 2/19/2013 5:16:24 PM |
| 修稿时间： | 2/26/2013 9:59:48 AM |
A Refrence-band-based Method for Removing Stripe Noise from HJ-1A HSI Images |
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| Gao Hai-liang,Gu Xing-f,Yu Tao,He Hua-ying,Wang Feng and Zhu Ling-ya.A Refrence-band-based Method for Removing Stripe Noise from HJ-1A HSI Images[J].Infrared,2013,34(3):7-11. |
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| Authors: | Gao Hai-liang Gu Xing-f Yu Tao He Hua-ying Wang Feng and Zhu Ling-ya |
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| Institution: | The State Key Laboratory of Remote Sensing Sciences,Institute of Remote Sensing Application,Chinese Academy of Sciences,The State Key Laboratory of Remote Sensing Sciences,Institute of Remote Sensing Application,Chinese Academy of Sciences,The State Key Laboratory of Remote Sensing Sciences,Institute of Remote Sensing Application,Chinese Academy of Sciences,China Centre for Resources Satellite Data and Application,Beijing,China Centre for Resources Satellite Data and Application,Beijing,China Centre for Resources Satellite Data and Application,Beijing |
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| Abstract: | The Hyper Spectral Imager (HSI) onboard the HJ-1A satellite has acquired a large quantity of image data since its launch in Sep. 2008. However, the effectiveness of those images is greatly limited because of the apparent stripe noise in the images acquired in partial bands of the HIS. According to the features of the image noise, a new method for removing the stripe noise by moving the windows based on a reference band is proposed. The result shows that this new noise removing algorithm can not only remove the stripe noise in the images effectively and improve the definition of the images remarkably, but also can retain the basic information
of the raw images. The method has the advantages of fast processing and wide range of application. It is an ideal stripe noise removing method. |
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| Keywords: | destripe hyperspectral remote sensing reference band HSI |
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