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Research on Algorithm of Vision-based Night Visibility Estimation

机译:基于视觉夜视可见性估算算法研究

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Accurately achieve the luminance of light sources at night images is significantly important to vision-based night visibility estimation. In this paper, we propose a practical night visibility algorithm. This algorithm contains two main parts, light sources recognition and edge extraction. Firstly, we give the model of vision-based visibility estimation, and propose the framework of algorithm. Secondly, we give the method to extract light sources from multiple potential targets by the prior knowledge of space information. Then, we analysis the features of light source image, and explain the expanded temple to cut sub-image of light source, and induce in PS level set to segment the edge. Experiments show that, the light source average recognition precision is approach to 0.95 at the condition of moderate breeze, and compared with the manual segment, the precision of light source segment is approach to 0.99 at the condition of real visibility larger than 500m.
机译:准确地实现夜间图像的光源的亮度对于视觉的夜视可视性估算显着重要。在本文中,我们提出了一种实用的夜晚可见度算法。该算法包含两个主要部件,光源识别和边缘提取。首先,我们给出了基于视觉的可见性估算的模型,并提出了算法框架。其次,我们通过现实的空间信息知识提供了从多个潜在目标中提取光源的方法。然后,我们分析光源图像的特征,并解释扩展的寺庙以切割光源的子图像,并在PS级别设置为段分割边缘。实验表明,光源平均识别精度在中等微风条件下逼近0.95,与手动段相比,光源段的精度在大于500米的实际可见度条件下接近0.99。

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