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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shulei Wu Liya Dong Huandong Chen Jinmei Zhan |
| Copyright Year | 2015 |
| Description | Author affiliation: Coll. of Inf. Sci. & Technol., Hainan Normal Univ., Haikou, China (Shulei Wu; Liya Dong; Huandong Chen) || Dept. of Inf. & Technol., Qiongtai Teachers Coll., Haikou, China (Jinmei Zhan) |
| Abstract | As the particularity of the mangrove ecosystem, it is difficult to do field investigation, which consumes much time, and the obtained data is not real-time. The technology of satellite remote sensing plays an important role in the detection of the ecological system. Some methods, such as band combination, expert classification and fuzzy classification, have been widely used in recent years. This paper explores the application of the image classification technology in mangrove information extraction based on RGB color only, and discusses the method of parallelepiped and Mean shift clustering respectively. According to the different image characteristics, the image classification technology based on RGB color only can distinguish the different research contents in remote sensing image, which uses a computer to analyze the target object quantitatively and classifies each image pixel or region into several categories. |
| Starting Page | 167 |
| Ending Page | 170 |
| File Size | 650417 |
| Page Count | 4 |
| File Format | |
| e-ISBN | 9781467386609 |
| DOI | 10.1109/CIS.2015.48 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-12-19 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Satellites Image color analysis image classification technology Information retrieval Classification algorithms Rivers Meanshift clustering method parallelepiped method Remote sensing satellite remote sensing Image classification |
| Content Type | Text |
| Resource Type | Article |
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