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- W2365348568 abstract "Current anomalous detection methods only depend on the spectral features in hyperspectral images.However,due to the improvement of spatial resolution of hyperspectral images,the relationship between neighborhood pixels can no longer be negligible.This paper proposes an anomalous detection method for hyperspectral images based on pixels′ neighborhood relationship.The aim is to make full use of the spatial information within the anomalous target.Firstly,the relationship of the neighborhood pixels in the hyperspectral images was described by the random field model.And the energy function was founded to reduce the range of detection.Then the inverse covariance matrix of the background in this model,which represents this neighborhood relationship information,was introduced into the local-region anomalous detector.Finally the detector used a sliding and nested dual window to detect probable anomalous pixels.The experiments show that the proposed method performs better than the current anomalous detection algorithm,especially for the larger anomalous targets which contain several neighborhood pixels." @default.
- W2365348568 created "2016-06-24" @default.
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- W2365348568 date "2010-01-01" @default.
- W2365348568 modified "2023-09-23" @default.
- W2365348568 title "An anomalous detection method for hyperspectral images based on neighborhood pixels" @default.
- W2365348568 hasPublicationYear "2010" @default.
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