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首页> 外文期刊>Chinese Journal of Electronics >Low Light Level Image Enhancement Based on Multi-layer Slicing Photon Localization Algorithm
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Low Light Level Image Enhancement Based on Multi-layer Slicing Photon Localization Algorithm

机译:基于多层切片光子定位算法的微光图像增强

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摘要

Low light level (LLL) images, which were captured by Intensified CCD (ICCD) camera equipped with an image intensifier, suffer low spatial resolution and contrast due to noise and dispersion. By dividing the integration time into intervals short enough, we obtain photon images where photon formed spots were nearly nonoverlapping. In order to enhance LLL images, we propose a Multi-layer slicing (MLS) photon localization algorithm based on photon images. The photon image is sliced by different planes. Photon spatial distribution (PSD) information is acquired by using projected area ratio, circularity and the number of slices. The enhanced LLL image is obtained by accumulating time-domain correlated PSD images. Experimental results show that the visual effects, spatial frequencies and contrast of the enhanced image are significantly improved.
机译:由配备有图像增强器的增强型CCD(ICCD)相机捕获的低光(LLL)图像由于噪声和色散而遭受低空间分辨率和对比度的困扰。通过将积分时间划分为足够短的间隔,我们可以获得光子形成的光斑几乎不重叠的光子图像。为了增强LLL图像,我们提出了一种基于光子图像的多层切片(MLS)光子定位算法。光子图像被不同平面切成薄片。通过使用投影面积比,圆度和切片数来获取光子空间分布(PSD)信息。通过累积时域相关的PSD图像获得增强的LLL图像。实验结果表明,增强图像的视觉效果,空间频率和对比度得到了明显改善。

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