-
The technology of applying the basic principles of graphics and image processing methods to adaptive camouflage has been widely used. Active image quality reconstruction adaptive camouflage technology is the use of image processing methods to reconstruct image quality through modulation functions such as stretching and distortion in the displayed image, matching the flexible display technology, and designing the surface material characteristics of the display device parameters, realize the change of the target's optical characteristics, and achieve the effect of camouflaging the target.
Using the constraint method to solve the image reconstruction problem, the objective function of image modulation can be characterized as[7]:
$$\phi (x) = \frac{1}{2}\left\| {y - \overrightarrow H x} \right\| + \lambda \varphi (x)$$ (1) Where, y is the degradation result of the ideal image x,
$\overrightarrow H $ is represent linear degradation,$\varphi (x)$ is a priori constraint imposed on the image, and$\lambda $ is the regularization parameter is used to adjust the proportion of the target function before and after. For the original image x, it can be characterized by the coefficients$\theta $ in the transform domain:$$x = \overrightarrow A \theta $$ (2) The image modulation problem is transformed as follows:
$$\tilde \theta = \arg {\min _\theta }\frac{1}{2}{\left\| {y - \overrightarrow H \overrightarrow A \theta } \right\|^2} + \lambda \varphi (\overrightarrow A \theta )$$ (3) There is, $\tilde x = \overrightarrow A \tilde \theta $ And
$\varphi (x)$ is equivalent to$TV(x)$ $$\varphi (x) = TV(x) = \sum\limits_{(i,j) \subset x} {\sqrt {{{\overrightarrow D }_h}{{(i,j)}^2} + {{\overrightarrow D }_v}{{(i,j)}^2}} } $$ (4) There, the horizontal gradient operator
${h_x} = $ $ {[01 - 1]^{\rm T}}$ , the vertical gradient operator${h_y} = {[10 - 1]^{\rm T}}$ .In recent years, flexible display technology has made great progress and development under the background of huge demand. Combined with the performance characteristics of flexible displays, the research and preparation of display devices with different performances are also changing with each passing day. In addition, materials that can achieve changes in spectral characteristics have been successfully developed and can be used for reference in related fields.
-
摘要: 基于柔性显示技术的主动像质重构自适应伪装方法是利用柔性显示器件结合频谱转移技术和主动像质重构技术实现目标表面光谱辐射特性的改变、转移和选择性分布。文中设计通过调制目标表面的光学特性参数改变目标的光学特征,可以实现目标在活动过程中实时拍摄背景图像,将其显示于柔性显示器上。利用主动像质重构、柔性显示和发射率控制层达到调制目标的红外辐射强度和有效分割目标热图的目的,从而实现全天候、全过程与周围的自然环境高度融合,并且,目标表面的光谱分布特征不随探测方向的变化而改变,达到目标伪装的效果,相较于改变目标表面的物理结构特征的方法,这样的技术使得目标的环境适应性更好,且易于实现。Abstract: The method of active image quality reconstruction adaptive camouflage based on flexible display technology is to use flexible display devices to combine spectrum transfer technology and active image quality reconstruction technology to achieve the change, transfer and selective distribution of the target surface spectral radiation characteristics. In this design, the optical characteristics of the target could be changed by modulating the optical characteristic parameters of the target surface, and the background image could be captured in real time during the activity of the target and displayed on the flexible display. The use of active image quality reconstruction, flexible display and emissivity control layer achieves the purpose of modulating the infrared radiation intensity of the target and effectively segmenting the target heat map, so as to achieve a high degree of integration with the surrounding natural environment throughout the weather and the whole process, and the spectrum of the target surface. The distribution characteristics do not change with the change of the detection direction, achieve the effect of target camouflage. Compared with the method of changing the physical structure characteristics of the target surface, this technique makes the target environment more adaptable and more survivability, and easy to implement.
-
Key words:
- camouflage /
- flexible display /
- image quality reconstruction /
- adaptive
-
-
[1] Huang Tao. Image reconstruction based on object modeling[D]. Xi'an: Xidian University, 2018. (in Chinese) [2] Wang Sha. Adaptive optimized sparse representation based compressed sensing reconstruction for remote sensing images[D]. Hangzhou: Zhejiang University, 2014. (in Chinese) [3] Huang Lingling, Wei Qunshuo, Wang Yongtian. Development and applications of wave-front modulation technology based on new functional metasurfaces [J]. Infrared and Laser Engineering, 2019, 48(10): 1002001. (in Chinese) doi: 10.3788/IRLA201948.1002001 [4] Chen Minghui, Wang Fan, Zhang Chenxi, et al. Sparse reconstruction of frequency domain OCT image based on compressed sensing [J]. Optics and Precision Engineering, 2020, 28(1): 189-199. (in Chinese) doi: 10.3788/OPE.20202801.0189 [5] Xiang Pengpeng. The research of super-resolution reconstruction algorithm for infrared image[D]. Shenzhen: Southern University of Science and Technology, 2016. (in Chinese) [6] Somayaji M, Christensen M P. Improving photon count and flat profiles of multiplex imaging systems with the odd-sysmmetric quadratic phase modulation mask [J]. Applied Optics, 2017, 46(18): 3754-3765. [7] Hale J S, Woollam J A. Prospects for IR emissivity control using electrochromic structures [J]. Thin Solid Films, 1999, 339: 174-180. [8] Liu Hongshun, Wang Zhe, Hu Qi, et al. Tomography technology based on spatial light modulator [J]. Chinese Optics, 2019, 12(6): 1338-1347. doi: 10.3788/CO.20191206.1338 [9] Hu Huiran, Dan Xizuo, Zhao Qihan, et al. Automatic extraction of speckle area in digital image correlation [J]. Chinese Optics, 2019, 12(6): 1329-1337. (in Chinese) doi: 10.3788/co.20191206.1329 [10] S Susan Yong. Super-resolution image reconstruction from aliased flir imagy[C]//Proceedings for the Army Science Conference(24th), 2004. [11] Alam M S, Bognar John G, Hardie R C, et al. Infrared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames [J]. IEEE Transactions on Instrumentation and Measurement, 2000, 49: 915-923. [12] Dai Shaosheng, Du Zhihui, Xiang Haiyan, et al. Reconstruction algorithm of super-resolution infrared image based on human vision processing mechanism [J]. Frontiers of Optoelectronics, 2015, 8(2): 195-202. doi: 10.1007/s12200-015-0440-z [13] Ma Yanxing, Wu Jian, Su Rongtao, et al. Review of optical phased array techniques [J]. Infrared and Laser Engineering, 2020, 49(10): 20201042. (in Chinese) doi: 10.3788/IRLA20201042 [14] Zhang Senhao, Qiu Donghai, Yi Ning, et al. Rapid preparation and medical application of wearable flexible electronics [J]. Optics and Precision Engineering, 2019, 27(6): 1362-1369. (in Chinese) doi: 10.3788/OPE.20192706.1362