| Super-resolution Restoration of Remote-sensing Images |
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| 作者姓名： | 刘扬阳 金伟其 苏秉华 陈华 张楠 |
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| 作者单位： | School of Information Science Technology, Beijing Institute of Technology, Beijing 100081, China |
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| 基金项目： | Sponsored by Doctor Foundation of Education Ministry of China （20020007006） |
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| 摘 要： | A novel image restoration scheme, which is super-resolution image restoration algorithm Poisson-maximum-afterword-probability based on Markvo constraint （MPMAP） combined with evaluating image detail parameter D, has been proposed. The advantage of super-resolution algorithm MPMAP incorporated with parameter D lies in the fact that superresolution algorithm MPMAP model is discrete, which is in accordance with remote-sensing imaging model, and the algorithm MPMAP is proved applicable to linear and non-linear imaging models with a unique solution when noise is not severe. According to simulation experiments for practical images, super-resolution algorithm MPMAP can retain image details better than most of traditional restoration methods; at the same time, the proposed parameter D can help to identify real point spread function （PSF） value of degradation process. Processing result of practical remote-sensing images by MPMAP combined with parameter D are given, it illustrates that MPMAP restoration scheme combined PSF estimation has a better restoration result than that of Photoshop processing, based on the same original images. It is proved that the proposed scheme is helpful to offset the lack of resolution of the original remote-sensing images and has its extensive application foreground.
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| 关 键 词： | 遥感技术 图像处理 图像恢复 分辨率 检波器 |
| 文章编号： | 1673-002X（2006）01-0043-04 |
| 收稿时间： | 2004-11-16 |
Super-resolution Restoration of Remote-sensing Images |
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| LIU Yang-yang,JIN Wei-qi,SU Bing-hua,CHEN Hua,ZHANG Nan.Super-resolution Restoration of Remote-sensing Images[J].Journal of China Ordnance,2006,2(1):43-46. |
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| Authors: | LIU Yang-yang JIN Wei-qi SU Bing-hua CHEN Hua ZHANG Nan |
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| Abstract: | A novel image restoration scheme, which is super-resolution image restoration algorithm Poisson-maximum-afterword-probability based on Markvo constraint (MPMAP) combined with evaluating image detail parameter D, has been proposed. The advantage of super-resolution algorithm MPMAP incorporated with parameter D lies in the fact that super-resolution algorithm MPMAP model is discrete, which is in accordance with remote-sensing imaging model, and the algorithm MPMAP is proved applicable to linear and non-linear imaging models with a unique solution when noise is not severe. According to simulation experiments for practical images, super-resolution algorithm MPMAP can retain image details better than most of traditional restoration methods; at the same time, the proposed parameter D can help to identify real point spread function (PSF) value of degradation process. Processing result of practical remote-sensing images by MPMAP combined with parameter D are given, it illustrates that MPMAP restoration scheme combined PSF estimation has a better restoration result than that of Photoshop processing, based on the same original images. It is proved that the proposed scheme is helpful to offset the lack of resolution of the original remote-sensing images and has its extensive application foreground. |
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| Keywords: | restoration image super-resolution remote-sensing images point spread function Images offset lack resolution application original estimation Photoshop Processing result value degradation process help identify real point spread function time retain better |
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