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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yang Kai-zhi Cheng Ying-lei Liu Jian |
| Copyright Year | 2011 |
| Description | Author affiliation: Telecommunication Engineering Institute, Air Force Engineering University, AFEU, Xi'an, China (Yang Kai-zhi; Cheng Ying-lei; Liu Jian) |
| Abstract | In order to extract available information from SAR image effectively, this paper proposes a method of texture feature extraction based on co-occurrence matrix. Based on the analysis of common attribute values of co-occurrence matrix, the method analyzes the influence of window size and displacement vector on texture feature. By comparing both distribution and mean value of different objects' texture feature, the research gets the best window size and displace vector to calculate co-occurrence matrix; determines practicable texture feature combination for classification, and advances the steps toward selecting and extracting the text feature in detail. The experiment results illustrate that the features extracted by the method are effective in describing objects. |
| Starting Page | 2038 |
| Ending Page | 2043 |
| File Size | 626112 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424493043 |
| e-ISBN | 9781424493067 |
| DOI | 10.1109/CISP.2011.6100654 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-10-15 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Histograms Noise feature extraction Support vector machine classification Filtering algorithms Feature extraction texture feature Vectors Data mining co-occurrence matrix SAR image |
| Content Type | Text |
| Resource Type | Article |
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