基于NSST域的红外和彩色可见光图像融合

邢雅琼, 王晓丹, 刘健, 毕凯

系统工程理论与实践 ›› 2016, Vol. 36 ›› Issue (2) : 536-544.

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PDF(2533 KB)
系统工程理论与实践 ›› 2016, Vol. 36 ›› Issue (2) : 536-544. DOI: 10.12011/1000-6788(2016)02-0536-09
论文

基于NSST域的红外和彩色可见光图像融合

    邢雅琼, 王晓丹, 刘健, 毕凯
作者信息 +

Fusion technique for infrared and color visible image in non-subsample shearlet transform domain

    XING Yaqiong, WANG Xiaodan, LIU Jian, BI Kai
Author information +
文章历史 +

摘要

为了进一步提升彩色可见光和红外图像的融合质量,提出了基于NSST和颜色空间的彩色图像融合方法.首先将RGB空间的彩色可见光图像变换到更符合人类视觉系统的颜色空间,其次利用NSST可以更好提取图像细节信息的优势,对颜色空间的非彩色分量和红外图像进行NSST分解,对分解后的低频系数采用基于方向信息测度的系数选择方案,对高频系数则采用基于隐马尔可夫树(hidden Markov tree, HMT)模型的系数选择方案,然后对经过选择融合的低、高频系数进行NSST逆变换,得到的融合图像作为新的非彩色分量,结合已有的分量将其逆变换回RGB空间,得到最终的融合图像.仿真实验证明了方法的有效性.

Abstract

In order to further improve the quality of color visible and infrared image fusion, the color image fusion method based on NSST and color space is proposed in this paper. First, the color visible image of RGB space needs to be transformated to space which is more in line with human visual system. Then take advantage of NSST which can extract the image detail information better to achieve the NSST decompositon of un-color component of space and infrared image. The options based on direction information measure are applied for the low frequency coefficient and the options based on hidden Markov tree (HMT) factor are for the high frequency coefficient. The final fusion image is obtained by the inverse transformation and back to its RGB space of the new un-color component which is the fusion image through NSST inverse transformation of low and high frequency coefficients in combination with the existing and components. The effictiveness of the method has been proved by the simulation results.

关键词

彩色 / 可见光 / 红外 / 图像融合

Key words

color / visible / infrared / image fusion

引用本文

导出引用
邢雅琼 , 王晓丹 , 刘健 , 毕凯. 基于NSST域的红外和彩色可见光图像融合. 系统工程理论与实践, 2016, 36(2): 536-544 https://doi.org/10.12011/1000-6788(2016)02-0536-09
XING Yaqiong , WANG Xiaodan , LIU Jian , BI Kai. Fusion technique for infrared and color visible image in non-subsample shearlet transform domain. Systems Engineering - Theory & Practice, 2016, 36(2): 536-544 https://doi.org/10.12011/1000-6788(2016)02-0536-09
中图分类号: TP312   

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基金

国家自然科学基金(60975026,61273275)
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