Conference proceeding
Improved fuzzy c-means algorithm and its application to classification of remote sensing image in Chengdu city, China
2016 International Conference on Progress in Informatics and Computing (PIC), pp.437-443
12/2016
DOI: 10.1109/PIC.2016.7949541
Abstract
The classification recognition performance is a hot study in the field of remote sensing image. In this paper, texture feature, shape feature, radiation intensity of remote sensing image information were used to initial terrain classification. Then an improved fuzzy c-means algorithm was applied on classification, and it included optimization of determine clustering center, got the number of clustering automatically and removed the noise of image after classification. Meanwhile, as an alternative to expert knowledge, data fusion method was used, which included the fusion of aeromagnetic data, gravity data and elevation data. The empirical results showed that this method can avoid the highly dependent on domain knowledge experts in image recognition and got a better classification effect in remote sensing image.
Details
- Title: Subtitle
- Improved fuzzy c-means algorithm and its application to classification of remote sensing image in Chengdu city, China
- Creators
- Dongmei Han - Shanghai University of Finance and EconomicsJiayu Ji - Shanghai University of Finance and EconomicsYonghui Dai - Shanghai University of International Business and EconomicsGuowei Li - Shanghai University of Finance and EconomicsWeiguo Fan - Shanghai University of Finance and EconomicsHuagen Chen - Tongji University
- Resource Type
- Conference proceeding
- Publication Details
- 2016 International Conference on Progress in Informatics and Computing (PIC), pp.437-443
- Publisher
- IEEE
- DOI
- 10.1109/PIC.2016.7949541
- Language
- English
- Date published
- 12/2016
- Academic Unit
- Business Analytics
- Record Identifier
- 9984380547402771
Metrics
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