典型伪装材料高光谱特征及识别方法研究

针对某些特定环境下，伪装目标和背景目标出现的“异物同谱”现象，传统的可见光及多光谱遥感伪装识别存在局限性，为此，将高光谱应用到典型伪装材料的特征分析与识别。以北方地区常用丛林迷彩伪装网为研究对象，利用SVC HR1024光谱仪获取其不同浸水时间的可见光-近红外光谱，通过光谱相似性度量和包络线去除处理，分析揭示不同浸水条件下伪装网和北方典型植被光谱特征和敏感波段，并基于近红外波段构建光谱比值指数RCI,用于识别绿色植被环境中的伪装目标，最后通过高光谱成像实验获取仿真伪装环境高光谱图像，并利用高光谱图像对识别效果进行验证。结果显示：(1)不同浸水时间的丛林迷彩伪装网的光谱曲线基本形态相似，且反射率随浸水时间的增加而整体呈下降趋势；1 900 nm波段是伪装网反射光谱对含水量响应最为明显的波段，其光谱特征会因浸水处理而相似于植被，相似度从0.895提高到了0.939。(2)丛林迷彩伪装网和植被在可见光波段的相似度较高，光谱波动情况相似，但在近红外波段光谱特征差异明显。通过包络线统去除分析得出970, 1 190和1 440 nm波段附近处是丛林迷彩伪装网识别的敏感波段，且基于迷彩伪装网和各植...

Research on Hyperspectral Features and Recognition Methods of Typical Camouflage Materials

Aiming at the phenomenon of “foreign objects with the same spectrum” in the camouflaged target and the background target in certain specific environments, traditional visible light and multi-spectral remote sensing technologies have limitations in camouflage recognition. This paper, applies hyperspectral technology to the characteristic analysis and recognition of typical camouflage materials. The SVC HR1024 spectrometer was used to obtain the Visible-NIR Spectrum of the jungle camouflage net under different water immersion times. The spectral characteristics and sensitive bands of the jungle camouflage net under different water immersion conditions and typical vegetation in northern China were analyzed and revealed through spectral similarity measurement and envelope removal treatment. Based on the near-infrared band, the spectral ratio index (RCI) was constructed to identify the camouflaged targets in the green vegetation environment. Finally, the hyperspectral image in the simulation camouflage environment was obtained through a hyperspectral imaging experiment, and the recognition effect was verified using the hyperspectral image. The results showed that: (1)The basic morphology of the spectral curve of the jungle camouflage net with different water immersion times was similar, and its reflectivity decreased as a whole with increasing water immersion time. The 1 900 nm band is the most obvious band that the reflectance spectrum of jungle camouflage net responds to water content, and its spectral characteristics are similar to those of vegetation due to water immersion treatment, and the similarity is increased from 0.895 to 0.939. (2)The similarity between camouflage net and vegetation is high in the visible band, and the spectral fluctuation is similar, but the spectral characteristics of the jungle camouflage net and vegetation are different in near-infrared band. Through the analysis of the envelope removal method, it is concluded that the bands around 970, 1 190 and 1 440 nm are sensitive bands for identifying the jungle camouflage net. Moreover, based on the two obvious differences in reflectance slope between the jungle camouflage net and the vegetation in the band range of 900~1 900 nm, RCI₁ (R_{1 190}/R_{1 270}) and RCI₂ (R_{1 270}/R_{1 440}) were constructed. (3) The decision tree classification model based on the RCI index can quickly and effectively extract the camouflaged target from the green vegetation background. Experimental results show that using the RCI index to identify and extract the camouflaged target area, the results obtained are in good agreement with the original image in shape and size, and the recognition accuracy can reach 95%, indicating that the index has a good recognition effect on camouflaged targets.