摘要
提出一种利用直觉模糊集评价红外伪装性能的方法。建立了伪装目标和背景红外图像的灰度值与直觉模糊集隶属度、非隶属度的关系;提出用Gamma函数作为隶属度函数,并用直觉模糊集方法重新描述红外图像;通过计算伪装前后直觉模糊集描述图像的三种模糊距离(Euclidean距离、Hamming距离以及Hausdoff距离)评价伪装效果。实验证明,用Gamma函数作为隶属度函数的直觉模糊集方法评价红外图像伪装具有很好的稳定性,且简单有效。
In this paper, a novel method using Atanassov＇s intuition fuzzy sets （A-IFS） for evaluating the infrared camouflage performance was proposed. According to the concept of A-IFS, it established the relationship between image gray scale with membership degree and non-membership degree Gamma function, as the membership function, was used to re-describing the camouflaged targets and backgrounds images. By calculating the fuzzy distances （ Euclidean distance, Hamming distance and Hausdoff distance） between camouflaged and under-camouflaged A-IFS images, the infrared camouflageperformance was obtained. Experiments show that, the Gamma function can describe the infrared camouflage image well, and as a method of evaluating the camouflage performance, A-IFS are stable, easy and very effective.
出处
《红外技术》
CSCD
北大核心
2012年第3期181-184,共4页
Infrared Technology
关键词
红外图像
直觉模糊集
隶属度
模糊距离
伪装评价
Infrared camouflage image, Atanassov＇s intuition fuzzy sets （A-IFS）, membership function, fuzzy distances, camouflage assessment
