Salient Local Binary Pattern for Ground-Based Cloud Classification

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  • Funds:

    Supported by the National Natural Science Foundation of China (61172103, 60933010, and 60835001).

  • doi: 10.1007/s13351-013-0206-8

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  • Ground-based cloud classification is challenging due to extreme variations in the appearance of clouds under different atmospheric conditions. Texture classification techniques have recently been introduced to deal with this issue. A novel texture descriptor, the salient local binary pattern (SLBP), is proposed for ground-based cloud classification. The SLBP takes advantage of the most frequently occurring patterns (the salient patterns) to capture descriptive information. This feature makes the SLBP robust to noise. Experimental results using ground-based cloud images demonstrate that the proposed method can achieve better results than current state-of-the-art methods.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Salient Local Binary Pattern for Ground-Based Cloud Classification

  • 1. State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190;
    State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190;
    State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190;
    State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190;
    State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences,Beijing 100190
Funds: Supported by the National Natural Science Foundation of China (61172103, 60933010, and 60835001).

Abstract: Ground-based cloud classification is challenging due to extreme variations in the appearance of clouds under different atmospheric conditions. Texture classification techniques have recently been introduced to deal with this issue. A novel texture descriptor, the salient local binary pattern (SLBP), is proposed for ground-based cloud classification. The SLBP takes advantage of the most frequently occurring patterns (the salient patterns) to capture descriptive information. This feature makes the SLBP robust to noise. Experimental results using ground-based cloud images demonstrate that the proposed method can achieve better results than current state-of-the-art methods.

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