地基可見光全天空云圖云量圖像處理識別方法
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成都信息工程大學科研基金(CRF201602)、國家自然科學基金(41305030)、公益性(氣象)行業專項(GYHY201106047)資助


Cloudiness Recognition Algorithm of GroundBased Visible AllSky Images Based on Image Processing
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    摘要:

    為增強地基可見光全天空云圖中云與天空的特征和區別,提高云檢測率,基于圖像復原和圖像增強技術提出一種改善云圖質量的方法。該方法采用暗通道去霧算法進行圖像復原;采用亮度直方圖均衡增強圖像紋理細節;綜合兩種方法,先圖像復原,再圖像增強。按低能見度薄云、低能見度厚云、高能見度薄云、高能見度厚云4種情況分別進行討論,結果表明:除高能見度薄云采用單一的圖像復原使云檢測效果降低外,圖像復原和圖像增強都能使云檢測和云量識別準確率提高;綜合二者,云檢測和云量識別準確率進一步提高;該方法對薄云和低能見度云圖的改善最為顯著。

    Abstract:

    In order to further distinguish the clouds and the background and improve cloud recognition, this paper proposes an algorithm to improve the quality of cloud images based on image restoration and enhancement techniques. First, a dark channel priordehazing algorithm is employed for image restoration. Then, the features are enhanced using the brightness histogram equalization algorithm. Finally, the two algorithms are combined by using image enhancement after image restoration. At the same time, the four conditions of thin cloud in low visibility, thick cloud in low visibility, thin cloud in high visibility, and thick cloud in high visibility are discussed, respectively. According to the simulation results, except that a single image restoration on thin clouds in high visibility has reduced cloud recognition, the proposed algorithm has significantly improved the image quality and cloud recognition. In addition, the image quality and cloud recognition can be further enhanced using the image restoration and enhancement techniques together, and there are more improvements on thin clouds and clouds in low visibility.

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陳青青,李彪,湯志亞,楊玲,王耀萱.地基可見光全天空云圖云量圖像處理識別方法[J].氣象科技,2017,45(6):1006~1010

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歷史
  • 收稿日期:2016-11-29
  • 定稿日期:2017-08-10
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  • 在線發布日期: 2017-12-28
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