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- W4367308081 abstract "Band selection is an important method for hyperspectral image(HSI) dimension reduction, which can greatly reduce the complexity of HSI analysis. Linear prediction algorithm is an unsupervised band selection algorithm with good classification effect. This paper uses Schmidt’s orthogonalization to improve it. Experiments prove that the optimized algorithm is consistent with linear prediction algorithm in band selection but much more efficient and the complexity of the optimized algorithm is in proportion to the number of selected bands." @default.
- W4367308081 created "2023-04-29" @default.
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- W4367308081 date "2023-04-28" @default.
- W4367308081 modified "2023-09-30" @default.
- W4367308081 title "Linear prediction band selection based on Schmidt orthogonalization for hyperspectral image" @default.
- W4367308081 doi "https://doi.org/10.1117/12.2674290" @default.
- W4367308081 hasPublicationYear "2023" @default.
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