Hyperspectral abnormal object detection method based on structure sparse representation and internal cluster filtering
A sparse representation, abnormal target technology, applied in the field of hyperspectral abnormal target detection, can solve the problem of low target detection efficiency, and achieve the effect of improving the detection rate
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[0032] The specific steps of the hyperspectral anomaly target detection method based on structural sparse representation and internal clustering filtering in the present invention are as follows:
[0033] Suppose the input hyperspectral image is a 3D data cube containing n b bands, each band is a picture of nrow row and n col The column size of the image. For the convenience of calculation, each band is stretched into a row vector, and all row vectors form a two-dimensional matrix X, Among them, each column of X represents the spectrum corresponding to each pixel, and this direction is the spectral dimension; each row of X corresponds to all pixel values of a band (ie n p =n row ×n col ), the direction is the spatial dimension. details as follows:
[0034] 1. Robust background dictionary learning based on principal component analysis.
[0035] (1) Use the double-window local RX algorithm to obtain the background pixel set.
[0036] According to the resolution of the...
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