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Content Provider | IEEE Xplore Digital Library |
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Author | Mishra, N.S. Ghosh, S. Ghosh, A. |
Copyright Year | 2012 |
Description | Author affiliation: Center for Soft Computing Research, Indian Statistical Institute, 203 B. T. Road, Kolkata - 700108, India (Ghosh, A.) || Department of Computer Science and Engineering, Jadavpur University, Kolkata - 700032, India (Ghosh, S.) || Department of Electronics and Communication Engineering, Netaji Subhash Engineering College, Kolkata - 700152, India (Mishra, N.S.) |
Abstract | Here we propose a methodology to combine the output of fuzzy clusterings to detect changes in remote sensing images. In this regard we select two fuzzy clustering algorithms, namely fuzzy c-means (FCM) and Gustafson Kessel clustering (GKC). For clustering purpose various image features are extracted using the neighborhood information of pixels from the difference image (DI). To assign a pixel-pattern to either of the two groups (for changed and unchanged regions of the DI) maximum of the two membership-values (given by FCM and by GKC for the same pattern for the same cluster) is considered. It has been observed experimentally that the changesare detected more efficiently using the proposed ensemble-based procedure. To show the effectiveness of the proposed technique, experiments are conducted on two multispectral and multitemporal remote sensing images. Results are compared with those of existing stand-alone fuzzy clustering based techniques, Markov random field (MRF) & neural network based algorithms and found to be superior. |
Starting Page | 279 |
Ending Page | 282 |
File Size | 824399 |
Page Count | 4 |
File Format | |
ISBN | 9781467318280 |
e-ISBN | 9781467318273 |
DOI | 10.1109/EAIT.2012.6407923 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-11-30 |
Publisher Place | India |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Visualization Multi-temporal images Shape Change detection algorithms Change detection Gustafson Kessel clustering Ensemble-based technique Remote sensing Satellites Fuzzy clustering Neural networks Clustering algorithms Fuzzy c-means clustering Combination of clustering |
Content Type | Text |
Resource Type | Article |
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