Cloud detection in all sky ConCam images by Gaussian fitting and valley detection in histogram

Tushar Jadhav, Aditi Kotibhaskar
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Abstract

Clouds are the complex part to classify in the all sky Continuous Camera (ConCam) image due to their intensity similar to other objects and their diverse nature. The paper presents a histogram based technique to extract clouds in ConCam images. Small scale features are extracted by subtracting Gaussian fitted histogram from original histogram of an image. Valleys are then detected in these small scale features and based on these valleys, i.e. their intensity levels, different regions of sky are classified.
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基于高斯拟合和直方图谷检测的全天空ConCam图像云检测
云是全天空连续相机(ConCam)图像中分类比较复杂的部分,因为云的强度与其他物体相似,且具有多样性。提出了一种基于直方图的图像云提取方法。小尺度特征提取方法是在原始图像的直方图上减去高斯拟合直方图。然后在这些小尺度特征中检测到谷,并根据这些谷,即它们的强度水平,对天空的不同区域进行分类。
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