Contourlet变换和遗传算法相结合的沥青红外图像增强方法
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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。
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.
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.
引文
[1]张玉存,侯新玉,林洪彬.基于红热图像测温技术的图像二维无网格消噪方法[J].计量学报,2015,36(4):379-383.Zhang Y C,Hou X Y,Lin H B. Image 2D meshless denoising method based on red thermal image temperature measurement technology[J]. Acta Metrologicala Sinica,2015,36(4):379-383.
[2]胡窦明,赵海生,李云川,等.一种基于同态滤波的红外图像增强新方法[J].红外技术,2012,34(4):224-228.Hu D M,Zhao H S,Li Y C,et al. A new infrared image enhancement method based on homomorphic filtering[J].Infrared Technology,2012,34(4):224-228.
[3]贾宏光,吴泽鹏,朱明超,等.基于广义线性运算和双边滤波的红外图像增强[J].光学精密工程,2013,21(12):3272-3282.Jia H G,Wu Z P,Zhu M C,et al. Infrared image enhancement based on generalized linear operation and bilateral filtering[J]. Optics and Precision Engineering,2013,21(12):3272-3282.
[4]占必超,吴一全,纪守新.基于平稳小波变换和Retinex的红外图像增强方法[J].光学学报,2010,30(10):2788-2793.Zhan B C, Wu Y Q, Ji S X. Infrared Image Enhancement Method Based on Stationary Wavelet Transform and Retinex[J]. Acta Optica Sinica,2010(10):2788-2793.
[5]秦翰林,周慧鑫,刘上乾,等.基于二代小波变换的红外图像非线性增强算法[J].光学学报,2009,29(2):353-356.Qin H Ln, Zhou H X, Liu S Q, et al. Nonlinear Enhancement Algorithm for Infrared Image Based on Second Generation Wavelet Transform[J]. Acta Optica Sinica,2009,29(2):353-356.
[6]彭洲,赵保军.基于Contourlet变换和模糊理论的红外图像增强算法[J].激光与红外,2011,41(6):635-640.Peng Z, Zhao B J. Infrared Image Enhancement Algorithm Based on Contourlet Transform and Fuzzy Theory[J]. LASER&IR,2011,41(6):635-640.
[7] Yuan L T, Swee S K, Ping T C. Infrared image enhancement using adaptive trilateral contrast enhancement[J]. Pattern Recognition Letters,2015,54:103-108.
[8] KaralA O,Okman O E,Ayta9 T. Adaptive image enhancement based on clustering of wavelet coefficients for infrared sea surveillance systems[J]. Infrared Physics&Technology,2011,54(5):382-394.
[9] Singh K,Kapoor R. Image enhancement using exposure based sub image histogram equalization[J]. Pattern Recognition Letters,2014,36:10-14.
[10] Anand S,Kumari R S S,Thivya T,et al. Sharpening enhancement of ultrasound images using contourlet transform[J]. Optik-International Journal for Light and Electron Optics,2013,124(21):4789-4792.
[11]吴凤和,孙迎兵,王鑫.基于爬山遗传算法的三坐标测量路径优化[J].计量学报,2016,37(3):235-240.Wu F H,Sun Y B,Wang X. Optimization of threecoordinate measurement path based on hill-climbing genetic algorithm[J]. Acta Metrologicala Sinica,2016,37(3):235-240.
[12]尚丽,苏品刚,周昌雄.应用轮廓波和稀疏编码收缩法消噪毫米波图像[J].计量学报,2012,33(2):166-171.Shang L,Su P G,Zhou C X. Denoising Millimeter Wave Image Using Contour Wavelet and Sparse Coding Shrinkage Method[J]. Acta Metrologicala Sinica,2012,33(2):166-171.
[13] Tubbs J D. A note on parametric image enhancement[J]. Pattern Recognition,1987,20(6):617-621.
[14]李奇,冯华君,徐之海,等.数字图像清晰度评价函数研究[J].光子学报,2002,31(6):736-738.Li Q,Feng H J,Xu Z H,et al. Study on the Evaluation Function of Digital Image Sharpness[J]. Acta Photonica Sinica,2002,31(6):736-738.
[15]张玉存,侯新玉.基于红外热图像的沥青路面温度离析区域检测方法[J].计量学报,2017,38(1):23-27.Zhang Y C,Hou X Y. Detection method of temperature isolation zone of asphalt pavement based on infrared thermal image[J]. Acta Metrologicala Sinica,2017,38(1):23-27.
[2]胡窦明,赵海生,李云川,等.一种基于同态滤波的红外图像增强新方法[J].红外技术,2012,34(4):224-228.Hu D M,Zhao H S,Li Y C,et al. A new infrared image enhancement method based on homomorphic filtering[J].Infrared Technology,2012,34(4):224-228.
[3]贾宏光,吴泽鹏,朱明超,等.基于广义线性运算和双边滤波的红外图像增强[J].光学精密工程,2013,21(12):3272-3282.Jia H G,Wu Z P,Zhu M C,et al. Infrared image enhancement based on generalized linear operation and bilateral filtering[J]. Optics and Precision Engineering,2013,21(12):3272-3282.
[4]占必超,吴一全,纪守新.基于平稳小波变换和Retinex的红外图像增强方法[J].光学学报,2010,30(10):2788-2793.Zhan B C, Wu Y Q, Ji S X. Infrared Image Enhancement Method Based on Stationary Wavelet Transform and Retinex[J]. Acta Optica Sinica,2010(10):2788-2793.
[5]秦翰林,周慧鑫,刘上乾,等.基于二代小波变换的红外图像非线性增强算法[J].光学学报,2009,29(2):353-356.Qin H Ln, Zhou H X, Liu S Q, et al. Nonlinear Enhancement Algorithm for Infrared Image Based on Second Generation Wavelet Transform[J]. Acta Optica Sinica,2009,29(2):353-356.
[6]彭洲,赵保军.基于Contourlet变换和模糊理论的红外图像增强算法[J].激光与红外,2011,41(6):635-640.Peng Z, Zhao B J. Infrared Image Enhancement Algorithm Based on Contourlet Transform and Fuzzy Theory[J]. LASER&IR,2011,41(6):635-640.
[7] Yuan L T, Swee S K, Ping T C. Infrared image enhancement using adaptive trilateral contrast enhancement[J]. Pattern Recognition Letters,2015,54:103-108.
[8] KaralA O,Okman O E,Ayta9 T. Adaptive image enhancement based on clustering of wavelet coefficients for infrared sea surveillance systems[J]. Infrared Physics&Technology,2011,54(5):382-394.
[9] Singh K,Kapoor R. Image enhancement using exposure based sub image histogram equalization[J]. Pattern Recognition Letters,2014,36:10-14.
[10] Anand S,Kumari R S S,Thivya T,et al. Sharpening enhancement of ultrasound images using contourlet transform[J]. Optik-International Journal for Light and Electron Optics,2013,124(21):4789-4792.
[11]吴凤和,孙迎兵,王鑫.基于爬山遗传算法的三坐标测量路径优化[J].计量学报,2016,37(3):235-240.Wu F H,Sun Y B,Wang X. Optimization of threecoordinate measurement path based on hill-climbing genetic algorithm[J]. Acta Metrologicala Sinica,2016,37(3):235-240.
[12]尚丽,苏品刚,周昌雄.应用轮廓波和稀疏编码收缩法消噪毫米波图像[J].计量学报,2012,33(2):166-171.Shang L,Su P G,Zhou C X. Denoising Millimeter Wave Image Using Contour Wavelet and Sparse Coding Shrinkage Method[J]. Acta Metrologicala Sinica,2012,33(2):166-171.
[13] Tubbs J D. A note on parametric image enhancement[J]. Pattern Recognition,1987,20(6):617-621.
[14]李奇,冯华君,徐之海,等.数字图像清晰度评价函数研究[J].光子学报,2002,31(6):736-738.Li Q,Feng H J,Xu Z H,et al. Study on the Evaluation Function of Digital Image Sharpness[J]. Acta Photonica Sinica,2002,31(6):736-738.
[15]张玉存,侯新玉.基于红外热图像的沥青路面温度离析区域检测方法[J].计量学报,2017,38(1):23-27.Zhang Y C,Hou X Y. Detection method of temperature isolation zone of asphalt pavement based on infrared thermal image[J]. Acta Metrologicala Sinica,2017,38(1):23-27.