Multi-sensor based infrared image super-resolution

WU Wei; WANG Mei-jie; LI Zhi; LI Kang-li; LIU Kai

doi:10.3788/OPE.20152313.0567

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Multi-sensor based infrared image super-resolution

更新时间：2020-08-13

- Multi-sensor based infrared image super-resolution
- Optics and Precision Engineering Vol. 23, Issue 10z, Pages: 566-575(2015)
- 作者机构：
  
  1. 四川大学电子信息学院,四川成都,610064
  2. 四川大学电气信息学院,四川成都,610064
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152313.0567
  CLC： TP391.4
- Received：08 May 2015，
  
  Revised：19 May 2015，
  
  Published：14 November 2015
- 稿件说明：
移动端阅览
吴炜, 王美洁, 李智等. 基于多传感器的红外图像超分辨[J]. 光学精密工程, 2015,23(10z): 566-575

WU Wei, WANG Mei-jie, LI Zhi etc. Multi-sensor based infrared image super-resolution[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 566-575
吴炜, 王美洁, 李智等. 基于多传感器的红外图像超分辨[J]. 光学精密工程, 2015,23(10z): 566-575 DOI： 10.3788/OPE.20152313.0567.

WU Wei, WANG Mei-jie, LI Zhi etc. Multi-sensor based infrared image super-resolution[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 566-575 DOI： 10.3788/OPE.20152313.0567.

摘要

利用可见光图像与红外图像之间存在的互补性和相关性

提出一种基于多传感器的红外图像超分辨方法。首先

利用自适应边缘检测算法提取红外图像边缘

并根据红外图像边缘与可见光图像对应区域的相关程度将红外图像边缘分为相关边缘和非相关边缘;然后

采用二次关系模型对相关边缘区域进行建模

通过该模型利用可见光信息估计红外图像的高频信息;最后

利用迭代反向投影法(IBP)对估计的高分辨率红外图像进行优化获得最终的高分辨率红外图像。实验结果表明

本文算法获得的小区图像

十字路口图像和道路图像的峰值信噪比(PSNR)分别比Choi算法高2.9 dB

1.44 dB和1.11 dB。另外

利用本文算法复原的红外图像具有更好的视觉效果

更逼真、更接近于原始高分辨率图像

复原出的高分辨率红外图像无论在主观效果上还是在客观评价指标上都取得了较好的结果。

Abstract

On the basis of complementary and relevance between a visible image and an infraved image

a new method which is called multi-sensor super resolution method was proposed. Firstly

an adaptive edge detection algorithm was used to extract the edges of the infrared image

and edges were divided into related edges and nonrelated edges according to the relevance of the edges of infrared image and corresponding visible image area. Then

a quadratic relationship model was built to estimate the high frequency patch of infrared image in the related edge region. At last

Iterative Back Projection(IBP) method was used to optimize the estimated super-resolved image. Experimental results indicate that the Peak Signal to Noise Ratios(PSNR) of the community image

crossroad image and the road image in this method are respectively 2.9 dB

1.44 dB and 1.11 dB

higher than that of the Choi algorithm. Experimental results also show that the proposed method enables reconstructing images to be better visual results and closely resembling the original high resolution images. The reconstructed images achieve better results on subjective visual effects and objective assessments.

关键词

Keywords

references

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LAI R, YANG Y T, ZHOU H X, et al..Total variation regularized iterative back-projection method for single frame image super resolution[C]. IEEE 11th International Conference on Singal Processing(ICSP),Beijing,2012:931-934.

吕侃,汤心溢,王世勇. 一种基于IBP的红外微扫描图像重建算法[J]. 红外技术, 2011,33(6):345-348. LÜ K, TANG X Y,WANG SH Y.An infrared microscanning image reconstruction algorithm based on IBP[J].Infrared Technology,2011,33(6):345-348.

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Related Institution

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

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Jiangxi Province Key Laboratory of Multidimensional Intelligent Perception and Control

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