Hyperspectral information can be used to express the material properties of objects, which has a strong effect on camouflage recognition. However, it is difficult to process it directly because of the huge hyperspectral image data. Therefore, this paper proposes a new band selection algorithm to achieve band selection by simulating visual perception. The subspace clustering self-attention adversarial network is constructed to realize the initial selection of band. According to the visual chromatic aberration principle, a model is constructed to determine the band that combines the strongest response intensity of a particular material, and then this band is selected as the final band, therefore realizing the algorithm of material demarcation in this way.

中文翻译：

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基于高光谱图像的材料鉴别算法

高光谱信息可以用来表达物体的材料特性，对伪装识别有很强的影响。然而，由于高光谱图像数据庞大，很难直接对其进行处理。因此，本文提出了一种新的波段选择算法，通过模拟视觉感知来实现波段选择。构建子空间聚类自注意力对抗网络，实现波段的初始选择。根据视觉色差原理，构建模型来确定结合特定材料响应强度最强的波段，然后选择该波段作为最终波段，从而实现了材料标定的算法。