Land cover classification of SPOT image by local majority voting

Jen Hon Luo, Din Chang Tseng

研究成果: 會議貢獻類型會議論文同行評審

摘要

We proposed a hierarchy scheme for the SPOT image land cover classification. In the first level, we combine the statistical classifier, maximum likelihood classification (MLC); the neural network classifier, Learning Vector Quantization (LVQ); and use a 3 × 3 window to extract second-order statistical features to classify the image. If the pixel can't reach the same label in this stage, it is processed in the second level. In the second stage, the first-order statistical features of each point in a window region are extracted. Then, the majority voting is used to label the pixel, the central point of the window, which is unclassified in the first level.

原文???core.languages.en_GB???
頁面2931-2933
頁數3
出版狀態已出版 - 2001
事件2001 International Geoscience and Remote Sensing Symposium (Igarrs 2001) - Sydney, NSW, Australia
持續時間: 9 7月 200113 7月 2001

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???event.eventtypes.event.conference???2001 International Geoscience and Remote Sensing Symposium (Igarrs 2001)
國家/地區Australia
城市Sydney, NSW
期間9/07/0113/07/01

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