Adaptive Graph Cut Based Cloud Detection in Wireless Sensor Networks
We focus on the issue of cloud detection in wireless sensor networks (WSN) and propose a novel detection algorithm named adaptive graph cut (AGC) to tackle this issue. We first automatically label some pixels as “cloud” or “clear sky” with high confidence. Then, those labelled pixels serve as hard c...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-10-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2015/947169 |
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| Summary: | We focus on the issue of cloud detection in wireless sensor networks (WSN) and propose a novel detection algorithm named adaptive graph cut (AGC) to tackle this issue. We first automatically label some pixels as “cloud” or “clear sky” with high confidence. Then, those labelled pixels serve as hard constraint seeds for the following graph cut algorithm. In addition, a novel transfer learning algorithm is proposed to transfer knowledge among sensor nodes, such that cloud images captured from different sensor nodes can adapt to different weather conditions. The experimental results show that the proposed algorithm not only achieves better results than other state-of-the-art cloud detection algorithms in WSN, but also achieves comparable results compared with the interactive segmentation algorithm. |
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| ISSN: | 1550-1477 |