Fusion of infrared polarization and intensity images using support value transform and fuzzy combination rules

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Wei, H. ORCID: https://orcid.org/0000-0002-9664-5748 and Yang, F. (2013) Fusion of infrared polarization and intensity images using support value transform and fuzzy combination rules. Infrared Physics & Technology, 60. pp. 235-243. ISSN 1350-4495

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To link to this item DOI: 10.1016/j.infrared.2013.05.008

Abstract/Summary

Infrared polarization and intensity imagery provide complementary and discriminative information in image understanding and interpretation. In this paper, a novel fusion method is proposed by effectively merging the information with various combination rules. It makes use of both low-frequency and highfrequency images components from support value transform (SVT), and applies fuzzy logic in the combination process. Images (both infrared polarization and intensity images) to be fused are firstly decomposed into low-frequency component images and support value image sequences by the SVT. Then the low-frequency component images are combined using a fuzzy combination rule blending three sub-combination methods of (1) region feature maximum, (2) region feature weighting average, and (3) pixel value maximum; and the support value image sequences are merged using a fuzzy combination rule fusing two sub-combination methods of (1) pixel energy maximum and (2) region feature weighting. With the variables of two newly defined features, i.e. the low-frequency difference feature for low-frequency component images and the support-value difference feature for support value image sequences, trapezoidal membership functions are proposed and developed in tuning the fuzzy fusion process. Finally the fused image is obtained by inverse SVT operations. Experimental results of visual inspection and quantitative evaluation both indicate the superiority of the proposed method to its counterparts in image fusion of infrared polarization and intensity images.

Item Type:	Article
Refereed:	Yes
Divisions:	Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:	32915
Uncontrolled Keywords:	Image fusion; Infrared polarization image; Fuzzy combination rule; Support value transform
Publisher:	Elsevier

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Fusion of infrared polarization and intensity images using support value transform and fuzzy combination rules

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