基于改进自适应分数阶微分的地面云图增强算法

Xiaoying Chen, Jie Kang, Cong Hu
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引用次数: 0

摘要

:地基云图的纹理丰富多样。许多云的纹理不像人工纹理那样清晰。提出了一种基于自适应分数阶微分的云图增强算法,用于提取地面可见云图的自然纹理。将Grunwald-Lentikov (G-L)和Grunwald-Lentikov (R-L)分数阶微分算子应用于地基云图的增强算法。设计了一种基于自适应微分阶的算子掩码。使用相应的掩码模板对每个像素进行处理。结果表明,该方法可以提取图像纹理和边缘细节,简化了微分阶选择过程。
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Ground Nephogram Enhancement Algorithm Based on Improved Adaptive Fractional Differentiation
: The texture of ground-based nephogram is abundant and multiplicity. Many cloud textures are not as clear as artificial textures. A nephogram enhancement algorithm based on Adaptive Fractional Differential is established to extract the natural texture of visible ground-based cloud image. Grunwald-Lentikov (G-L) and Grunwald-Lentikov (R-L) fractional differential operators are applied to the enhancement algorithm of ground-based nephogram. An operator mask based on adaptive differential order is designed. The corresponding mask template is used to process each pixel. The results show that this method can extract image texture and edge details and simplify the process of differential order selection.
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