Hyperspectral Target Detection Based on Spectral Weighting
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Target detection has become an important research direction in hyperspectral imagery (HSI) processing. In this paper, aiming at the phenomenon that different bands have different abilities to distinguish materials, a spectral weighting detection algorithm is proposed. Firstly, relative distance between different categories as the spectral separability criterion is used to estimate the distinction ability of each band. And then different bands are endowed with different weighting coefficients. Finally, the RX and LPD algorithms are used to test the efficiency of the proposed spectral weighting method. The experimental results show that the detection algorithms based on spectral weighting have better performances than the traditional RX and LPD algorithms.
KeywordsHyperspectral imagery Target detection Spectral separability criterion Spectral weighting
This work is supported by the National Nature Science Foundation of China (61801075), the Fundamental Research Funds for the Central Universities (3132019218).
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