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- W45276225 abstract "This paper proposes an automatic unsupervised method for change detection at pixel level of Landsat-5 TM images based on spectral angle mapper (SAM). In most existing studies, conventional use of SAM does not take into account contextual information of a pixel. The proposed method incorporates spatio-contextual information both at feature and decision level for improved change detection accuracy. First, a similarity image is created using context-sensitive spectral angle mapper, and then it is segmented into two segments changed and unchanged using k-means algorithm to create a change map. The quantitative as well as qualitative comparison of the experiment results shows that the proposed method gives better results than the other existing method." @default.
- W45276225 created "2016-06-24" @default.
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- W45276225 date "2014-01-01" @default.
- W45276225 modified "2023-09-27" @default.
- W45276225 title "An Automatic Unsupervised Method Based on Context-Sensitive Spectral Angle Mapper for Change Detection of Remote Sensing Images" @default.
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- W45276225 doi "https://doi.org/10.1007/978-3-319-14717-8_12" @default.
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