Contourlet变换和遗传算法相结合的沥青红外图像增强方法

doi:10.3969/j.issn.1000-1158.2019.01.05

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摘要沥青施工过程中,采集的红外图像容易受到周围环境噪声的影响,使图像变得模糊、信噪比低,从而导致后续图像处理分析的准确度降低。针对该噪声特性,提出了一种Contourlet变换和遗传算法相结合的红外图像增强方法。首先对原始红外图像进行Contourlet变换,得到带有多尺度、多方向信息的带通子带,然后对其进行模糊增强,并通过自适应遗传算法优化模糊增强参数,最后对增强后的带通子带进行Contourlet逆变换,得到效果增强的红外图像。实验结果表明,与其它几种常用的红外图像增强方法相比,此方法能更有效地抑制噪声,提高清晰度,取得了较好的增强效果。

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	朱丹丹
	王斌
	杨奕
	李永勃

关键词 ：计量学, 红外图像增强, 图像处理, Contourlet变换, 遗传算法

Abstract：As the construction process of asphalt, the collected infrared images are susceptible to the ambient noise, making the image blurred and the SNR low, which leads to decrease the accuracy of the subsequent image processing analysis. Basing on the noise characteristic, a method of combining contourlet transform with genetic algorithm of infrared image enhancement are proposed. Firstly, the original infrared image is subjected to contourlet transform, and the bandpass subband with the multi-scale and multi-directional information is obtained. Then, the bandpass subband carries on the fuzzy enhancement.The fuzzy enhancement parameters are optimized by adaptive genetic algorithm. Finally, the contourlet inverse transform is used in the enhanced bandpass subband, obtain the enhanced infrared image. The experimental results show that compared with other commonly used infrared image enhancement methods, this method can effectively suppress the noise, improve the clarity, and achieve a better enhancement effect.

Key words： metrology infrared image enhancement image processing contourlet transform genetic algorithm

收稿日期: 2017-03-02 发布日期: 2019-01-07

PACS:

TB942

基金资助:河北省交通运输厅科技计划项目(Y-131114)

通讯作者: 王斌 E-mail: 1017821869@qq.com

作者简介: 朱丹丹(1978-),女,满族,辽宁葫芦岛人,燕山大学副教授,主要从事红外检测、红外热图像处理方面的研究。Email: hfwang@ysu.edu.cn

引用本文:

朱丹丹,王斌,杨奕,李永勃. Contourlet变换和遗传算法相结合的沥青红外图像增强方法[J]. 计量学报, 2019, 40(1): 25-30.
ZHU Dan-dan,WANG Bin,YANG Yi,LI Yong-bo. Asphalt Infrared Image Enhancement of Combining Contourlet Transform with Genetic Algorithm. Acta Metrologica Sinica, 2019, 40(1): 25-30.

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