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1)  Weak image
微弱光学图像
2)  very feeble light detection
极微弱光图像探测
3)  Ultra-weak bioluminesence image
生物超微弱发光图像
4)  ultra weak builuminescence image
超微弱生物发光图像
1.
An ultra sensitive imaging system was developed and used to obtain the ultra weak builuminescence image of a living Kunming mouse, and statistical analysis was used for studying photon frequency distribution.
应用超高灵敏度的光电成像系统,获得了活体昆明鼠的超微弱生物发光图像,并用概率统计理论研究了光子图像中的光子频数分布,得到了一种去除噪声的原则。
5)  optical image differentiation
光学图像微分
6)  low-light-level image
微光图像
1.
The degradation of low-light-level image mainly depends on sensitivity,non-linearity and noise of detectors.
微光图像的退化主要取决于探测器的灵敏度、非线性和噪声。
2.
As the noise of low-light-level image can be removed efficiently and low-light-level image quality can be improved by low-light-level video real-time image processor, which has quality of super speed and real time, observation distance of low-light-level video observation system becomes far.
微光视频图像实时处理器以其具有的高速实时处理优点,可以有效地消除微光图像噪声,改善微光图像的像质,从而提高了微光视频观察系统的观察视距,这无论是在军用和民用上都有很广泛的使用价值。
3.
For the characteristics of infrared images for the target image focused on the distribution of gray,low-light-level grayscale image is relatively uniform distribution,a image fusion method is proposed in this paper,that is extracting infrared thermal targets firstly,and then fused to low-light-level image as the background.
针对红外图像中目标图像灰度分布集中,微光图像灰度分布相对均匀的特点,提出了一种先提取红外图像中的热目标,然后以微光图像为背景进行图像融合的方法。
补充资料:高光谱分辨率遥感图像及图像光谱信息提取


高光谱分辨率遥感图像及图像光谱信息提取


  高光谱分辨率遥感图像及图像光谱信息提取 郑兰芬供稿
  
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