中国激光, 2014, 41 (9): 0909001, 网络出版: 2014-08-15   

基于对比度增强的红外与可见光图像融合

Contrast Enhanced Fusion of Infrared and Visible Images
周渝人 1,2,*耿爱辉 1,3王莹 1,2陈娟 1,4张强 1
作者单位
1 中国科学院长春光学精密机械与物理研究所, 吉林 长春130033
2 中国科学院大学, 北京 100039
3 长春理工大学理学院, 吉林 长春 130022
4 长春工业大学电气与电子工程学院, 吉林 长春130012
摘要
为提高低亮度红外与可见光图像融合的视觉效果,提出了一种对比度增强的图像融合算法。使用双边滤波器对光照进行估计,提出了双边滤波子带分解多尺度Retinex变换,并在此基础上对原图像进行子带分解。使用基于局部空间频率的细节增强融合策略完成子带内系数融合,使用全局方差加权融合策略完成子带间系数融合。使用非线性拉伸法将融合结果由对数域映射到显示域。实验结果表明,该方法可有效消除光晕,提高融合图像清晰度,使细节信息更突出。
Abstract
A contrast enhanced image fusion algorithm is proposed to improve the visual effect of fused image from infrared and visible images at low lightness. Estimating background luminance by bilateral filter, the subband-decomposed multiscale Retinex with bilateral filtering is proposed, and original images are decomposed using proposed transformation. Coefficient matrixes in the same subband are fused by using detail enhancement strategy based on local space frequency, and fused coefficient matrixes in different subbands are fused by global variance weighted sum. The fusion result is needed for the transition from the logarithmic domain to the display domain by improved nonlinear stretching. The results of experiments demonstrate that the proposed algorithm can effectively overcome the halo phenomenon, improving definition of fused image, and the detail information is more salient.
参考文献

[1] 张德祥, 高清维, 陈军宁. 基于小波变换纹理一致性测度的遥感图像融合算法[J]. 仪器仪表学报, 2007, 28(1): 158-162.

    Zhang Dexiang, Gao Qingwei, Chen Junning. Remote sensing image fusion algorithm using texture homogeneity measure based on wavelet transform[J]. Chinese Journal of Scientific Instrument, 2007, 28(1): 158-162.

[2] 郭明, 符拯, 奚晓梁. 基于局部能量的NSCT域红外与可见光图像融合算法[J]. 红外与激光工程, 2012, 41(8): 2229-2235.

    Guo Ming, Fu Zheng, Xi Xiaoliang. Novel fusion algorithm for infrared and visible images based on local energy in NSCT domain[J]. Infrared and Laser Engineering, 2012, 41(8) :2229-2235.

[3] 韩亮, 李婵飞, 蒲秀娟. 图像分割与平稳小波变换法融合红外与可见光图像[J]. 重庆大学学报, 2013, 36(6): 112-118.

    Han Liang, Li Chanfei, Pu Xiujuan. Fusion method for infrared and visible light images based on image segmentation and stationary wavelet transform[J]. Journal of Chongqing University, 2013, 36(6): 112-118.

[4] 柴勇, 何友, 曲长文. 基于亚像素区域加权能量特征的多尺度图像融合算法[J]. 光学学报, 2009, 29(10): 2732-2737.

    Chai Yong, He You, Qu Changwen. Multiscale image fusion algorithm based on subpixel weighted region energy[J]. Acta Optica Sinica, 2009, 29(10): 2732-2737.

[5] 杨粤涛, 朱明, 贺柏根, 等. 采用改进投影梯度非负矩阵分解和非采样Contourlet变换的图像融合方法[J]. 光学 精密工程, 2011, 19(5): 1143-1150.

    Yang Yuetao, Zhu Ming, He Baigen, et al.. Fusion algorithm based on improved projected gradient NMF and NSCT[J]. Optics and Precision Engineering, 2011, 19(5): 1143-1150.

[6] 冯鑫, 王晓明, 党建武, 等. 基于Shearlet变换的红外与可见光图像融合[J]. 光电子·激光, 2013, 24(2): 384-390.

    Feng Xin, Wang Xiaoming, Dang Jianwu, et al.. Fusion of infrared and visible images based on Shearlet transform[J]. Journal of Optoelectronics Laser, 2013, 24(2): 384-390.

[7] 张雷, 李婧, 李根全, 等. 一种新的基于图像增强的融合算法[J]. 激光与红外, 2013, 43(9): 1072-1075.

    Zhang Lei, Li Jing, Li Genquan, et al.. Novel fusion algorithm based on image enhancement[J]. Laser and Infrared, 2013, 43(9): 1072-1075.

[8] Melkamu H Asmare, Vijanth S Asirvadam, Lila Iznita. Multi-sensor image enhancement and fusion for vision clarity using contourlet transform[C]. International Conference on Information Management and Engineering, 2009, 112: 352-356.

[9] 吴泽鹏, 宣明,贾宏光, 等. 基于最优映射曲线的红外图像动态范围压缩和对比度增强方法[J]. 中国激光, 2013, 40(12): 1209002.

    Wu Zepeng, Xuan Ming, Jia Hongguang, et al.. Infrared image dynamic range compression and contrast enhancement based on optimal mapping curve[J]. Chinese J Lasers, 2013, 40(12): 1209002.

[10] Jingli Gao, Bo Li, Yidong Bao, et al.. Wavelet enhanced fusion algorithm for multisensor images[C]. International Conference on Consumer Electronics, Communications and Networks, 2011. 5474-5476.

[11] Fan Xu, Xiuqin Su. An enhanced infrared and visible image fusion method based on wavelet transform[C]. International Conference on Intelligent Human-Machine Systems and Cybernetics, 2013, 255: 453-456.

[12] J H Jang, B Choi, S D Kim, et al.. Sub-band decomposed multiscale retinex with space varying gain[C]. IEEE International Conference on Image Processing, 2008. 3168-3171.

[13] J H Jang, S D Kim, J B Ra. Enhancement of optical remote sensing images bysubband-decomposed multiscale retinex with hybrid intensity transfer function[J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(5): 983-987.

[14] J H Jang, Y Bae, J B Ra. Multi-sensor image fusion using subband decomposed multiscale retinex[C]. IEEE International Conference on Image Processing, 2009. 2177-2180.

[15] J H Jang, Y Bae, J B Ra. Contrast-enhanced fusion of multisensory images using subband-decomposed multiscale retinex[J]. IEEE Transactions on Image Processing, 2012, 21(8): 3479-3490.

[16] 王龙志, 姚晓天, 孟卓, 等. 基于自适应多尺度Retinex的光学相干层析图像衰减补偿算法[J]. 中国激光, 2013, 40(12): 1204001.

    Wang Longzhi, Yao Xiaotian, Meng Zhuo, et al.. An optical coherence tomography attenuation compensation algorithm based on adaptive multi-scale retinex[J]. Chinese J Lasers, 2013, 40(12): 1204001.

[17] Tomasi C, Manduchi R. Bilateral filtering for gray and color images[C]. IEEE International Conference on Computer Vision, 1998. 839-846.

[18] Han Y, Cai Y Z, Cao Y, et al.. A new image fusion performance metric based on visual information fidelity[J]. Information Fusion, 2013, 14(2): 127-135.

周渝人, 耿爱辉, 王莹, 陈娟, 张强. 基于对比度增强的红外与可见光图像融合[J]. 中国激光, 2014, 41(9): 0909001. Zhou Yuren, Geng Aihui, Wang Ying, Chen Juan, Zhang Qiang. Contrast Enhanced Fusion of Infrared and Visible Images[J]. Chinese Journal of Lasers, 2014, 41(9): 0909001.

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