Spectral Camouflage Characteristics and Recognition Ability of Targets Based on Visible/Near-Infrared Hyperspectral Images

Abstract

Hyperspectral imaging can simultaneously obtain the spatial morphological information of the ground objects and the fine spectral information of each pixel. Through the quantitative analysis of the spectral characteristics of objects, it can complete the task of classification and recognition of ground objects. The appearance of imaging spectrum technology provides great advantages for military target detection and promotes the continuous improvement of military reconnaissance levels. At the same time, spectral camouflage materials and methods that are relatively resistant to hyperspectral reconnaissance technology are also developing rapidly. In order to study the reconnaissance effect of visible/near-infrared hyperspectral images on camouflage targets, this paper analyzes the spectral characteristics of different camouflage targets using the hyperspectral images obtained in the visible and near-infrared bands under natural conditions. Two groups of experiments were carried out. The first group of experiments verified the spectral camouflage characteristics and camouflage effects of different types of camouflage clothing with grassland as the background; the second group of experiments verified the spectral camouflage characteristics and camouflage effects of different types of camouflage paint sprayed on boards and steel plates. The experiment shows that the hyperspectral image based on the near-infrared band has a good reconnaissance effect for different camouflage targets, and the near-infrared band is an effective “window” band for detecting and distinguishing true and false targets. However, the stability of the visible/near-infrared band detection for the target identification under camouflage paint is poor, and it is difficult to effectively distinguish the object materials under the same camouflage paint. This research confirms the application ability of detection based on the visible/near-infrared band, and points out the direction for the development of imaging detectors and camouflage materials in the future.

EXNet: (2+1)D Extreme Xception Net for Hyperspectral Image Classification

“…Given such advantages, HSI has extensive application across various real-world domains. This includes environmental studies [3], [4], atmospheric research [5], [6], agriculture [7], forestry [8], assessments of water quality and contamination [9], mineral exploration, food processing and quality assessment [10]- [17], medical applications [18]- [21], and even military domains [22], [23].…”

Three-Layered Thin Films for Simultaneous Infrared Camouflage and Radiative Cooling

“…Recently, multilayered thin films have emerged that efficiently tune the radiative properties of materials [5][6][7][8][9][10][11]. As a type of metamaterial, multilayered thin films are composed of two or more stack-arranged dielectric materials, which have great potential for applications in perfect absorbers (PAs) [5,[11][12][13][14], radiative cooling [15][16][17][18][19] and IR camouflage [20][21][22][23][24][25][26][27][28]. While the investigation of individual functionalities is progressively advancing, the exploration of multilayered thin films that can be compatible with diverse functionalities is thriving.…”

High Light Efficiency Spectral Polarization Imaging Method Based on Mach–Zehnder Structured Liquid Crystal Tunable Filters and Variable Retarders

“…Spectral polarization imaging (SPI) aims to obtain four-dimensional (4D) representation data of target scenes, consisting of two-dimensional (2D) spatial information, onedimensional spectral information, and the polarization state information represented by full-Stokes parameters [1,2]. Due to the its ability to reveal and retrieve target information, e.g., material composition, surface texture and characteristic details, SPI has been extensively applied in many night-vision-related fields, such as anomaly detection, field reconnaissance, night navigation, and so on [3][4][5][6][7][8][9][10].…”