模糊逻辑与特征差异驱动的红外偏振图像融合模型

安富; 杨风暴; 牛涛

红外技术, 2014, 36 (4): 304, 网络出版: 2014-05-04

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

论文大纲

安富杨风暴牛涛

作者单位

中北大学信息与通信工程学院, 山西太原 030051

图像融合特征差异驱动模糊逻辑红外偏振 image fusion feature difference driving fuzzy logic infrared polarization

摘要

利用 non-subsampled contourlet transform(NSCT)对红外偏振与红外光强图像进行分解, 得到源图像的低频子带和高频方向子带。通过对红外偏振和光强图像差异特征的分析, 对低频选取局部能量和局部信息熵提取差异特征, 然后利用模糊逻辑融合低频子带的不确定区域, 利用特征差异驱动来融合低频子带的确定区域；对高频选取局部边缘信息保留量和局部方差提取差异特征, 然后利用模糊逻辑融合高频方向子带的不确定区域, 利用特征差异驱动来融合高频方向子带的确定区域。最后利用 NSCT对高低频子带进行逆变换得到最后的融合图像。从而建立起基于模糊逻辑与特征差异驱动的红外偏振图像融合模型。实验仿真结果表明, 该融合模型可融合源图像互补的差异特征, 使其在目标识别和分类中具有一定的应用价值。

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.

参考文献

[1] Nedelcu A, Guériaux V, Berurier A, et al. Multispectral and polarimetric imaging in the LWIR:Intersubband detector a versatile solution[C]//Proceedings of the International Conference on Quantum Structure Infrared Photodetector, 2013, 59: 125-132.

[2] 高永芳, 时家明, 许波, 等. 地面目标的热红外伪装技术研究 [J].航天电子对抗, 2011, 27(4): 20-21.

[3] Lavigne D A, Breton M, Fournier G, et al. Target discrimination of man-made objects using passive polarimetric signatures acquired in the visible and infrared spectral bands[C]//Proceedings of SPIE on Polarization Science and Remote Sensing V, 2011, 8160: 816007, doi: 10.1117/12.894055.

[4] 赵劲松. 偏振成像技术的进展 [J].红外技术, 2013, 35(12): 743-750.

[5] 陈伟力, 王霞, 金伟其, 等. 基于小波包变换的中波红外偏振图像融合研究[J].北京理工大学学报, 2011, 31(5):579-582.

[6] 杨风暴, 李伟伟, 蔺素珍, 等. 红外偏振与红外光强图像的融合研究[J].红外技术, 2011, 33(5): 262-266.

[7] 李伟伟, 杨风暴, 安富. 基于 NSCT的红外偏振与光强图像的融合研究[J].光电技术应用, 2012, 27(2): 58-61.

[8] 南京理工大学. 一种基于小波的红外偏振图像自适应融合方法 :中国, CN201110457969.8[P]. 2012-7-11.

[9] 黄晓青. 基于模糊逻辑的红外与可见光图像融合技术 [D].重庆: 重庆大学, 2012.

[10] 安富, 杨风暴, 蔺素珍, 等. 特征差异驱动的红外偏振与光强图像融合 [OL]. [2013-03-20].中国科技论文在线, [2013-03-20]. http://www. paper. edu. cn/releasepaper/content/201303-725.

[11] Lavigne D A, Breton M. A new fusion algorithm for shadow penetration using visible and midwave infrared polarimetric images[C]//13th Conference on Information Fusion, 2010: 1-7.

[12] Ren Xianyi, Zheng Yijun, Hu Tao, et al. Image fusion based on NSCT and fuzzy logic[C]//2010 International Conference on Multimedia Technology(ICMT), 2010, doi: 10.1109/ ICMULT. 2010. 5631292.

[13] Xydeas C S, Petrovi V. Objective image fusion performance measure[J]. Electronics Letters, 2000, 36(4): 308-309.

[14] 苏伍各, 陶忠祥, 董博, 等. 边缘信息的红外与可见光图像融合评价[J].火力与指挥控制, 2012, 37(1): 194-197.

[15] Yang Bin, Li Shutao. Pixel-level image fusion simultaneous orthogonal matching pursuit[J]. Information Fusion, 2012, 13(1): 10-19.

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, 36(4): 304. AN Fu, YANG Feng-bao, NIU Tao. A Fusion Model of Infrared Polarization Images Based on Fuzzy Logic and Feature Difference Driving[J]. Infrared Technology, 2014, 36(4): 304.

模糊逻辑与特征差异驱动的红外偏振图像融合模型

关于本站 Cookie 的使用提示

全站搜索

模糊逻辑与特征差异驱动的红外偏振图像融合模型

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索