Name
Abstract | ||
|---|---|---|
Cloud detection for remote sensing images is often a necessary process, because cloud is widespread in optical remote sensing images and causes a lot of difficulty to many remote sensing activities, such as land cover monitoring, environmental monitoring and target recognizing. In this paper, a novel cloud detection method is proposed for multispectral remote sensing images from Landsat 8. Firstly, the color composite image of Bands 6, 3 and 2 is divided into superpixel sub-regions through Simple Linear Iterative Cluster (SLIC) method. Then, a two-step superpixel classification strategy is used to predict each superpixel as cloud or non-cloud. Thirdly, a fully connected Conditional Random Field (CRF) model is used to refine the cloud detection result, and accurate cloud borders are obtained. In the two-step superpixel classification strategy, the bright and thick cloud superpixels, as well as the obvious non-cloud superpixels, are firstly separated from potential cloud superpixels through a threshold function, which greatly speeds up the detection. The designed double-branch PCA Network (PCANet) architecture can extract the high-level information of cloud, then combined with a Support Vector Machine (SVM) classifier, the potential superpixels are correctly classified. Visual and quantitative comparison experiments are conducted on the Landsat 8 Cloud Cover Assessment (L8 CCA) dataset; the results indicate that our proposed method can accurately detect clouds under different conditions, which is more effective and robust than the compared state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/rs10060877 | REMOTE SENSING |
Keywords | Field | DocType |
cloud detection,multispectral remote sensing,superpixel,PCA network,conditional random field | Conditional random field,Computer vision,Support vector machine,Composite image filter,Multispectral pattern recognition,Artificial intelligence,Geology,Classifier (linguistics),Land cover,Cloud cover,Cloud computing | Journal |
Volume | Issue | Citations |
10 | 6 | 3 |
PageRank | References | Authors |
0.38 | 24 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yue Zi | 1 | 7 | 0.84 |
| Fengying Xie | 2 | 182 | 15.33 |
| Zhiguo Jiang | 3 | 321 | 45.58 |