Because of the continuous advancement of spectral imaging technology, the spectral fineness of hyperspectral remote sensing images increases continually, and the scale of band data enlarges constantly, it is more and more difficult to process multi-dimensional data. Band selection has been applied in many fields as an effective way of data dimensionality reduction, however, the relatively single experimental data used by the existing common methods, the ability to discriminate when applied to specific objects such as camouflage targets cannot be verified. Therefore, when the research uses the band selection method to solve the problem of large amount of data and band redundancy in hyperspectral images, how to quantitatively calculate the significance of the camouflage target has become an urgent problem. The image evaluation index of simulated vision is introduced, and the quantitative results are used to show the effectiveness of the selected method for identifying the target, which provides theoretical support and thinking reference for the establishment of an algorithm model suitable for the recognition of camouflage targets in the battlefield environment.
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