基于矩匹配和变分方法的MODIS条带去除模型
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解放军理工大学气象海洋学院研一队,解放军理工大学气象海洋学院遥感中心,解放军理工大学气象海洋学院

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国家自然科学基金项目(面上项目,重点项目,重大项目)


Destriping Model of MODIS Image Based on Moment Matching and Variational Approach
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College of Meteorology and Oceanography, PLA Univ. of Sci. & Tech,College of Meteorology and Oceanography, PLA Univ. of Sci.,College of Meteorology and Oceanography, PLA Univ. of Sci.

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The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    针对MODIS影像条带噪声的特点,提出了一种结合矩匹配和变分方法的条带去除模型。首先采用矩匹配方法去除多行和宽行条带噪声,然后基于改进的条带检测方法定位矩匹配后的残余条带,最后基于变分条带去除模型,使用Split Bregman迭代求解以去除条带。实验结果表明,该方法能够有效地去除MODIS影像中的条带噪声,并能有效地保持图像中的细节信息。与直方图匹配、矩匹配、低通滤波及单向变分去条带算法相比,本文模型取得了更为理想的去噪效果。

    Abstract:

    A novel model for stripe noise reduction was proposed by combining moment matching with variational method, based on analyzing the characteristics of stripe noises in moderate resolution imaging spectroradiometer (MODIS) data. Firstly, multi-line and wide-line stripes were denoised by the moment matching method. Secondly, the stripes left in the result image were located by the improved stripe detection algorithm. Finally, based on the variational destrping model, Split Bregman iteration was adopted to reduce the strip noises. Experimental results show that the proposed algorithm can remove stripes in MODIS data and preserve the details of the image effectively. Compared with the destriping models including histogram matching, moment matching, low-pass filter and unidirectional variational destriping, the proposed method obtained more ideal results.

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胡宝鹏,周则明,孟勇.基于矩匹配和变分方法的MODIS条带去除模型[J].红外,2014,35(11):28-36.

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