| 航天光学遥感器信噪比的人工神经网络评价 |
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| 引用本文： | 李宏壮,田园,韩昌元,吴国栋,马冬梅. 航天光学遥感器信噪比的人工神经网络评价[J]. 光电工程, 2006, 33(4): 44-49 |
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| 作者姓名： | 李宏壮 田园 韩昌元 吴国栋 马冬梅 |
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| 作者单位： | 中国科学院长春光学精密机械与物理研究所,吉林,长春,130022;中国科学院研究生院,北京,100039;中国科学院长春光学精密机械与物理研究所,吉林,长春,130022 |
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| 摘 要： | 提出基于人工神经网络进行航天光学遥感器信噪比评价的方法,首先对航天遥感图像进行分析,从图像中将与景物结构和噪声有关的特征向量分别提取出来,作为ANN的输入。网络通过对大量信噪比已知的图像样本训练后,可完成对航天光学遥感器传输下来的任意一幅地面景物图像进行系统的信噪比测试,从而避免了采用特定景物目标进行测量中的诸多弊端,测量平均误差低于10%。
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| 关 键 词： | 航天光学遥感器 信噪比 人工神经网络 |
| 文章编号： | 1003-501X(2006)04-0044-06 |
| 收稿时间： | 2005-05-16 |
| 修稿时间： | 2005-11-15 |
Assessment of signal-to-noise ratio of space optical remote sensor using artificial neural network |
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| LI Hong-zhuang,TIAN Yuan,HAN Chang-yuan,WU Guo-dong,MA Dong-mei. Assessment of signal-to-noise ratio of space optical remote sensor using artificial neural network[J]. Opto-Electronic Engineering, 2006, 33(4): 44-49 |
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| Authors: | LI Hong-zhuang TIAN Yuan HAN Chang-yuan WU Guo-dong MA Dong-mei |
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| Affiliation: | 1. Changchun Institute of Optics, Fine Mechanics and Physics, the Chinese Academy of Sciences Changchun 130022, China; 2. Graduate School of the Chinese Academy ofSciences, Beijing 100039, China |
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| Abstract: | On the basis of artificial neural network (ANN), a new method to assess the signal-to- noise ratio (SNR) of space optical remote sensor is proposed. Through analyzing the images of space remote sensor, the eigenvectors related to the structure of landscape and noise were abstracted respectively, and then these eigenvectors were used as the input of ANN. After being trained with simulated images whose SNR were known, the ANN could assess the SNR of unknown images. This method can avoid the defects that special views were needed, and the mean assessment error is less than 10%. |
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| Keywords: | Space optical remote sensor Signal to noise ratio (SNR) Artificial neural network(ANN). |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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