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Infrared polarization image fusion based on combination of NSST and improved PCA


 

YANG Feng-bao, DONG An-ran, ZHANG Lei, JI Lin-na

 

(School of Information and Communication Engineering, North University of China, Taiyuan 030051, China)

 

Abstract: In view of the problem that current mainstream fusion method of infrared polarization image—Multiscale Geometry Analysis method only focuses on a certain characteristic to image representation. And spatial domain fusion method, Principal Component Analysis (PCA) method has the shortcoming of losing small target, this paper presents a new fusion method of infrared polarization images based on combination of Nonsubsampled Shearlet Transformation (NSST) and improved PCA. This method can make full use of the effectiveness to image details  expressed by NSST and the characteristics that PCA can highlight the main features of images. The combination of the two methods can integrate the complementary features of themselves to retain features of targets and image details fully. Firstly, intensity and polarization images are decomposed into low frequency and high frequency components with different directions by NSST. Secondly, the low frequency components are fused with improved PCA, while the high frequency components are fused by joint decision making rule with local energy and local variance. Finally, the fused image is reconstructed with the inverse NSST to obtain the final fused image of infrared polarization. The experiment results show that the method proposed has higher advantages than other methods in terms of detail preservation and visual effect.

 

Key words: image fusion; infrared image; polarization image; nonsubsampled shearlet transformation (NSST); principal component analysis (PCA)

 

CLD number: TP391Document code: A

 

Article ID: 1674-8042(2016)02-0176-09  doi: 10.3969/j.issn.1674-8042.2016.02.014

 

References

 

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基于NSST和改进PCA相结合的红外偏振图像融合

 

杨风暴, 董安冉, 张雷, 吉琳娜

 

(中北大学 信息与通信工程学院, 山西 太原 030051)

 

摘要:针对当前红外偏振图像融合的主流方法——多尺度几何分析法对图像表示只侧重某一方面的特点和空间域融合方法主成分分析法(PCA)易丢失小目标的缺点的问题, 本文提出一种基于非下采样剪切波变换(NSST)和改进PCA相结合的红外偏振图像融合方法。 该方法能充分利用NSST对图像细节表示的有效性和PCA能突出主要特征的特点, 综合二者的互补性, 充分保留不同源图像的目标和细节特征。 首先用NSST将源红外光强和偏振图像分解为低频和不同方向的高频分量; 其次, 低频分量用改进的PCA进行融合, 高频分量用局部能量和局部方差联合进行决策融合; 最后, 用NSST逆变换重构融合图像, 得到最终红外偏振融合结果图。 实验结果表明, 本文方法在细节保留和视觉效果等方面较其它方法均有较高优势。

 

关键词:图像融合; 红外图像; 偏振图像; NSST; PCA

 

引用格式:YANG Feng-bao, DONG An-ran, ZHANG Lei, et al. Infrared polarization image fusion based on combination of NSST and improved PCA. Journal of Measurement Science and Instrumentation, 2016, 7(2): 176-184. [doi: 10.3969/j.issn.1674-8042.2016.02.014]

 

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