The Effect Evaluation of Infrared Camouflage Simulation System Based on Visual Similarity

doi:10.3969/j.issn.1000-1093.2017.02.020

Abstract

Abstract: An evaluation method based on visual similarity is presented to solve the difficulty in the effect evaluation of infrared camouflage simulation system. From the perspective of visual similarity, a new visual similarity model is proposed, and the evaluation index system, including temperature deviation coefficient, discrete deviation coefficient and visual similarity coefficient, is established. A multi-attribute decision making (MADM) model based on intuitionistic fuzzy sets for evaluation is built to reduce the influence of subjective experience. The technique for order preference by similarity to an ideal solution (TOPSIS) is used to solve the model. For the same distance to idea/anti-idea alternative, the grey approach coefficient based on intuitionistic fuzzy sets and the Hamming distance is used to describe the similarity between the alternatives, solving the MADM problem effectively. The application example shows that the evaluated results of the proposed model are consistent with the evaluated results of TOPSIS method and experts, thus verifying the reasonability of evaluation index system and the feasibility of the proposed method. Key

Key words: ordnancescienceandtechnology, effectevaluation, camouflage, visualsimilarity, intuitionisticfuzzysets, TOPSIS, greycorrelation

CLC Number:

E951.4

FANG Hao, LI Ai-hua, PAN Yu-long, WANG Xue-jin, JIANG Ke, WANG Hua. The Effect Evaluation of Infrared Camouflage Simulation System Based on Visual Similarity[J]. Acta Armamentarii, 2017, 38(2): 351-357.

References

［1］查亚兵, 唐见兵. 基于主观综合评判的作战仿真可信度评估方法研究[J]. 国防科技大学学报, 2010, 32(6): 153-157.
ZHA Ya-bing, TANG Jian-bing. Research on a credibility evaluation method for warfare simulation based on the subject integrate judgment [J]. Journal of National University of Defense Technology, 2010, 32(6): 153-157. (in Chinese)
[2] 黄柯棣, 赵鑫业, 杨山亮,等. 军事分析仿真评估系统关键技术综述[J].系统仿真学报, 2012, 24(12): 2439-2447.
HUANG Ke-di, ZHAO Xin-ye, YANG Shan-liang, et al. System design description infrastructure overview for military simulation and analysis system [J]. Journal of System Simulation, 2012, 24(12): 2439-2447. (in Chinese)
[3］侯旺, 梅风华, 陈国军,等. 基于背景最佳滤波尺度的红外图像复杂度评价准则[J]. 物理学报, 2015, 64(23):234202.
HOU Wang, MEI Feng-hua, CHEN Guo-jun, et al. An evaluation criterion of infrared image complexity based on background optimal filter scale [J]. Acta Physica Sinica, 2015, 64(23): 234202. (in Chinese)
[4] 娄树理, 韩艳丽, 任建存,等. 基于结构相似度和保真度的红外成像传感器仿真评价方法研究[J]. 红外, 2015, 30(2): 30-35.
LOU Shu-li, HAN Yan-li, REN Jian-cun, et al. Research on evaluation method of simulation of infrared imaging sensor based on structural similarity and fidelity [J]. Infrared, 2015, 30(2): 30-35. (in Chinese)
[5] 吕绪良, 林伟, 许卫东,等. 应用迭代自组织数据分析技术模糊聚类法划分伪装效能等级[J]. 兵工学报, 2005,26(5): 681-684.
LYU Xu-liang, LIN Wei, XU Wei-dong, et al. Applying the fuzzy clustering analysis of ISODATA to the classification of camouflage effectiveness [J]. Acta Armamentarii, 2005, 26(5): 681-684. (in Chinese)
[6］ Atanassov K T. Intuitionistic fuzzy sets[J]. Fuzzy Sets & Systems, 1986, 20(1):87-96.
[7] 张英俊, 马培军, 苏小红,等. 属性权重不确定条件下的区间直觉模糊多属性决策[J]. 自动化学报, 2012, 38(2): 220-228.
ZHANG Ying-jun, MA Pei-jun, SU Xiao-hong, et al. Multi-attribute decision making with uncertain attribute weight information in the framework of interval-valued intuitionistic fuzzy set [J]. Acta Automatic Sinica, 2012, 38(2): 220-228. (in Chinese)
[8］万树平. 直觉模糊性多属性决策综述[J]. 控制与决策, 2010, 25(11):1601-1606.
WAN Shu-ping. Survey on intuitionistic fuzzy multi-attribute decision making approach [J]. Control and Decision, 2010, 25(11): 1601-1606. (in Chinese)
[9] Hwang C L, Yoon K S. Multiple attribute decision making methods and applications: a state-of-the-art survey[M]. Berlin: Springer-Verlag, 1981.

[10] Wang Z, Bovik A C, Sheikh H R, et al. Image quality assessment: from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 2004, 13(4):600-612.
[11] Sheikh H R, Bovik A C. Image information and visual quality[J]. IEEE Transactions on Image Processing, 2006, 15(2):430-44.
[12] Sheikh H R, Bovik A C, Veciana G D. An information fidelity criterion for image quality assessment using natural scene statistics[J]. IEEE Transactions on Image Processing, 2005, 14(12):2117-2128.
[13］ Zhang L, Zhang D, Mou X. RFSIM: a feature based image quality assessment metric using Riesz transforms [C]∥Proceedings of 17th IEEE International Conference on Image Process. Hong Kong: IEEE, 2010:321-324.
[14] Zhang L, Shen Y, Li H. VSI: a visual saliency-induced index for perceptual image quality assessment.[J]. IEEE Transactions on Image Processing, 2014, 23(10):4270-4281.
[15］ Zhang L,Gu Z,Li H. SDSP: A novel saliency detection method by combining simple priors [C]∥Proceedings of 20th IEEE International Conference on Image Process.Melbourne, Australia: IEEE, 2013: 171-175.
[16] Zhang L, Zhang L, Mou X, et al. FSIM: a feature similarity index for image quality Assessment[J]. IEEE Transactions on Image Processing, 2011, 20(8):2378-2786.
[17］刘思峰, 蔡华, 杨英杰,等. 灰色关联分析模型研究进展[J]. 系统工程理论与实践, 2013, 33(8): 2041-2046.
LIU Si-feng, CAI Hua, YANG Ying-jie, et al. Advance in grey incidence analysis modeling [J]. Systems Engineering-Theory & Practice, 2013, 33(8): 2041-2046. (in Chinese)
[18] 邓聚龙. 灰理论基础[M]. 武汉:华中科技大学出版社, 2004: 26-34.
DENG Ju-long. A textbook of grey system theory [M]. Wuhan: Huazhong University of Science & Technology Press, 2004: 26-34. (in Chinese)
[19］宁小磊, 吴颖霞, 于天朋,等. 基于改进灰色关联分析的仿真模型综合验证方法[J]. 兵工学报, 2016, 37(2): 339-347.
NING Xiao-lei, WU Ying-xia, YU Tian-peng, et al. Research on comprehensive validation of simulation models based on improved grey relational analysis [J]. Acta Armamentarii, 2016, 37(2): 339-347. (in Chinese)

第38卷第2期2017 年2月兵工学报ACTA
ARMAMENTARIIVol.38No.2Feb.2017

[1]	YANG Di, ZHOU Ying, XIE Zhenping. Evaluation Method for Dynamic Effect of Camouflage Based on Battlefield Environment Twinning [J]. Acta Armamentarii, 2024, 45(1): 349-362.
[2]	WANG Dong, GAO Qinhe, HUANG Tong, LIU Zhihao, GAO Lei. Dynamic Evaluation of Vehicle Camouflage Effect Based on Saliency Characterization in Complex Background [J]. Acta Armamentarii, 2023, 44(6): 1620-1631.
[3]	JIANG Xinhao, CAI Wei, ZHANG Zhili, JIANG Bo, YANG Zhiyong, WANG Xin. Camouflaged Object Segmentation Based on COSNet [J]. Acta Armamentarii, 2023, 44(5): 1456-1468.
[4]	SUN Haiwen， YU Shaozhen， JIANG Yuan, ZHOU Mo， TANG Jiayu， LI Dan. Target Threat Assessment Method for UAV Swarm at Sea [J]. Acta Armamentarii, 2022, 43(S2): 32-39.
[5]	ZHOU Bojun， YU Chuanqiang， LIU Zhihao， KE Bing. Rapid Erection Technology and Verification of Special Vehicles Based on High-Voltage Energy Storage [J]. Acta Armamentarii, 2022, 43(7): 1488-1497.
[6]	GAO Yueguang, FENG Shunshan, LIU Yunhui, HUANG Qi. Initial Velocity Distribution of Fragments from Cylindrical Charge Shells with Different Thick End Caps [J]. Acta Armamentarii, 2022, 43(7): 1527-1536.
[7]	DENG Liyuan, YANG Ping, LIU Weidong, WANG Jiangpeng. Application in Damage Effect Evaluation of Early Warning Radar of Cloudy Bayesian Network Based on Dempster Shafer/AnalyticHierarchy Process Method [J]. Acta Armamentarii, 2022, 43(4): 814-825.
[8]	ZHOU Ying， XIE Zhenping， JIANG Xiaojun. Simulation Design of Camouflage Target Concealing Strategy Based on Evolutionary Computation [J]. Acta Armamentarii, 2021, 42(9): 1987-1997.
[9]	LI Shurui， DUAN Zhuoping， ZHENG Baohui， LUO Guan， HUANG Fenglei. Cylinder Test and Equation of State for DNAN-based Aluminized Melt-cast Explosive [J]. Acta Armamentarii, 2021, 42(7): 1424-1430.
[10]	YU Songlin， CHEN Yuhua， HE Hu， WANG Jijun， LI Yan. Background Selection Method of Optical Camouflage Effect Evaluation Based on Color Clustering [J]. Acta Armamentarii, 2021, 42(3): 617-624.
[11]	YANG Hui, HE Chao, PAN Jialiang, JIA Qi, HE Meng, XU Xin. Application of Electro-thermal Coating in Infrared Decoy [J]. Acta Armamentarii, 2021, 42(1): 118-123.
[12]	YANG Xin, XU Weidong, JIA Qi. A Dynamic Camouflage Effect Evaluation Method Based on Feature Statistics [J]. Acta Armamentarii, 2019, 40(8): 1693-1699.
[13]	MA Shixin, LIU Chuntong, LI Hongcai, WANG Hao, HE Zhenxin. Camouflage Effect Evaluation Based on Hyperspectral Image Detection and Visual Perception [J]. Acta Armamentarii, 2019, 40(7): 1485-1494.
[14]	LI Zhonghua， YU Jun， HU Zhiyi， KANG Qinyu， GAO Shouyi， LIAN Zhichao， XIAO Feng. A method of Stitching Digital Camouflage Patterns on Different Planes Based on Texture Synthesis and Best Seam Line Algorithm [J]. Acta Armamentarii, 2019, 40(3): 666-672.
[15]	CAI Yunxiang， SHI Lei， TIAN Zhenxi. A Digital Pattern Design Method Based on Equipment Three-dimensional Model [J]. Acta Armamentarii, 2019, 40(11): 2296-2303.