红外技术Issue(4)：304-310,7.
模糊逻辑与特征差异驱动的红外偏振图像融合模型
A Fusion Model of Infrared Polarization Images Based on Fuzzy Logic and Feature Difference Driving
摘要
Abstract
Infrared polarization and infrared intensity images are decomposed by non-subsampled contourlet transform(NSCT)to get the low-frequency sub-bands and high-frequency directional sub-bands of source images in this paper. Analyzing the differences between infrared polarization image and intensity image, and using local energy and local information entropy to extract the difference features of the low-frequency sub-bands,we merge the area of uncertainty and the area of certainty of low-frequency sub-bands respectively by fuzzy logic and feature differences driving. Difference features are extracted from high-frequency directional sub-bands by local edge information preservation and local variance, and then the area of uncertainty and the area of certainty of high-frequency directional sub-bands are merged respectively by fuzzy logic and feature difference driving. Finally, by the NSCT inverse transformation of the high and low frequency sub-bands, the final fused image is obtained. Therefore, the fusion model of infrared polarization images based on fuzzy logic and feature difference driving is established. The simulation results show that the fusion model can integrate the complementary difference features and it has certain application value in the target identification and classification.关键词
图像融合/特征差异驱动/模糊逻辑/红外偏振Key words
image fusion/feature difference driving/fuzzy logic/infrared polarization分类
信息技术与安全科学引用本文复制引用
安富,杨风暴,牛涛..模糊逻辑与特征差异驱动的红外偏振图像融合模型[J].红外技术,2014,(4):304-310,7.基金项目
教育部高等学校博士学科点专项科研资助项目博导类资助课题，编号20121420110004；山西省回国留学人员科研资助项目，编号20120706ZX。 （）
