## 4 Establishment of Simulated HSI Dataset Based on Experimental Measurement
### Measurement Process and Results  
Due to the similarity in the spectral characteristics for some bands of the same color ground objects, a common disadvantage of traditional pixel-by-pixel classifiers based on spectral information is \"salt and pepper noise\" [13]. In order to solve the above problems, this paper selects ground objects with similar colors to analyze, process and classify the hyperspectral reflectance data. Spectroscopic measurements were performed in a dark room with vegetation samples placed on an angle-adjustable stage. When measuring the sample, after each measurement point, move the sample by an appropriate distance or replace it with a new sample of the same type and continue to measure until the reflectance data of 240 different points are collected. The acquisition results are shown in Figure 5a, and Figure 5b is the average reflectance of the sample in the visible light range. It is worth noting that the purpose of this paper is to propose and verify a DR method that is more suitable for the classification of samples with close spectral characteristics, so the scope of the study is narrowed to the vicinity of the visible light where the spectrum of the ground object is closest. However, in practical applications, in order to give full play to the advantages of the wide spectral response range of HSI, the full range should be used as much as possible to improve the classification accuracy.  
Clove leaves, shrub leaves and grass leaves have typical vegetation spectral reflectance characteristics. In the visible light range of 450-750 nm, the reflectance is at a low level. The smaller reflection peak at 550 nm is the \"green peak\", and its characteristics are mainly affected by the chlorophyll content of vegetation leaves. After 700 nm, the reflectivity rises rapidly, which is within the red-light range, so it is called the \"red edge\" phenomenon of  
Figure 5: (**a**) Reflectance of all measurement points; (**b**) average reflectance of samples.  
vegetation. It is the position where the reflectance of vegetation leaves changes the fastest, which is mainly affected by the structure of vegetation cells.  
As shown in Figure 5a, the spectral numbers of the data samples of the same class show the same curve trend, but there are differences in the values within a certain range. The main reason is the variability of the sample material. For example, the camouflage cloth is composed of four kinds of color blocks (pigments), and the physical performance at different points of the sample is non-uniform, so the spectrum at different points of the same type of objects changes in amplitude. This results in the existence of different degrees of intersection between the spectra of ground objects. On the contrary, the spectrum of green coating with a single material and uniform spraying is very concentrated. Comparing the reflectance curves of the artificial object samples and the vegetation leaves, it can be found that the green artificial objects and the vegetation leaves are generally very similar in the visible light range, showing a lower reflectance spectrum and a reflection peak near 550 nm. After 700 nm, due to the red edge phenomenon of vegetation, the reflectivity of vegetation and human-made objects is significantly different. In practice, there are a large number of mixed pixels in HSIs. The existence of mixed pixels will further enhance the similarity between ground object samples.