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结合NSST和颜色对比度增强的彩色夜视方法

Color Night Vision Method Combining NSST with Color Contrast Enhancement

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摘要

针对夜视图像彩色融合通常存在细节信息不够丰富、颜色对比度低的问题,为了获得更为理想的彩色融合效果,提出一种新的基于非下采样剪切波变换(Non-subsampled Shearlet Transform,NSST)和颜色对比度增强的彩色融合方法。首先,分别设计基于S 函数和局部方向对比度的低频与高频融合规则,完成源可见光与红外图像在NSST 域的融合;其次,将灰度融合图像赋给Y 分量,源图像的差值信号赋给U 和V 色差分量,形成YUV 空间的伪彩色融合图像。最后,选择一幅与待上色图像具有相似颜色分布的自然日光图像作为彩色参考图像,在YUV空间对伪彩色融合图像进行颜色对比度增强的非线性色彩传递。与近年方法相比,该方法所得彩色融合效果细节信息丰富、热目标突出。将该方法运用于彩色夜视领域,可有效增强场景深度感知和目标的可探测性。

Abstract

Traditional color night vision fusion methods usually suffered from the problems of blurry visual effects and the low color contrast between the target and the background, in order to obtain the more ideal color fusion effect, an improved color fusion method based on Non-subsampled Shearlet Transform (NSST) and color contrast enhancement was proposed. Firstly, NSST was employed to decompose the infrared and visible source images, respectively, and then the gray-level fusion image was obtained according to the self-adaptive fusion rules based on the S function and the local directional contrast. Secondly, the gray fusion image was assigned to the Y component, and the difference of the source images was respectively assigned to the U and V component, and then the false color fusion image was generated in YUV space. Finally, a natural daylight color image with similar color feature to the gray fusion image was selected as the reference image, meanwhile, transferring the color feature of the reference image to the false color fusion image based on the nonlinear color transfer technique in the uncorrelated YUV space, so as to enhance the color contrast of the hot target and cold background. Compared with the methods in recent years, Experimental results showed that the color fusion result based on ours contained more abundant details, and the hot target was highlighted. This method is applied to the field of color night vision that can make for enhancing the situation awareness and improve the target detectability.

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中图分类号:TP391

DOI:10.3969/j.issn.1003-501x.2016.11.014

所属栏目:图像与信号处理

基金项目:国家自然科学基金资助项目(61170185);航空科学基金资助项目(2015ZC54008);辽宁省教育厅科研项目(L2015411);辽宁省教育厅科研项目(L201605);校青年人才成才基金项目(201406Y)

收稿日期:2016-03-23

修改稿日期:2016-05-03

网络出版日期:--

作者单位    点击查看

吴燕燕:沈阳航空航天大学 工程训练中心,沈阳 110136
王亚杰:沈阳航空航天大学 工程训练中心,沈阳 110136
石祥滨:沈阳航空航天大学 工程训练中心,沈阳 110136
王琳霖:沈阳航空航天大学 工程训练中心,沈阳 110136

联系人作者:吴燕燕(pursuit1989@126.com)

备注:吴燕燕(1989-),女(汉族),河南开封人。硕士,助理实验师,主要研究工作是图像处理、图像融合、计算机视觉。

【1】薛模根,周浦城,刘存超. 夜视图像局部颜色传递算法 [J]. 红外与激光工程,2015,44(2):782-785.
XUE Mogen,ZHOU Pucheng,LIU Cunchao. A novel local color transfer method for night vision image [J]. Infrared and Laser Engineering,2015,44(2):782-785.

【2】谷雨,刘晶红,孙明超,等. 基于分形特征和导引滤波的可见光与红外图像融合算法 [J]. 光电工程,2015,42(4):62-67.
GU Yu,LIU Jinghong,SUN Mingchao,et al. Visible and Infrared Image Fusion Algorithm by Fractal Feature and Guided Filtering [J]. Opto-Electronic Engineering,2015,42(4):62-67.

【3】YIN Songfeng,CAO Liangcai,LING Yongshun,et al. One color contrast enhanced infrared and visible image fusion method [J]. Infrared Physics and Technology(S1350-4495),2010,53(2):146-150.

【4】Toet A. Natural colour mapping for multiband night vision imagery [J]. Information Fusion(S1566-2535),2003,4(3):155-166.

【5】李光鑫,徐抒岩,赵运隆,等. 颜色传递技术的快速彩色图像融合 [J]. 光学 精密工程,2010,18(7):1638-1647.
LI Guangxin,XU Shuyan,ZHAO Yunlong,et al. Fast color image fusion based on color transfer technique [J]. Optics and Precision Engineering,2010,18(7):1638-1647.

【6】QIAN Xiaoyan,WANG Yujin,WANG Bangfeng. Effective contrast enhancement method for color night vision [J]. Infrared Physics & Technology(S1350-4495),2012,55(1):130-136.

【7】GUO Kanghui,Labate D. Optimally sparse multidimensional respresentation using shearlets [J]. SIAM Journal on Mathematical Analysis(S1095-7154),2007,39(1):298-318.

【8】张鸿杰,王宪,孙子文. Shearle 多方向自适应加权融合的稀疏表征人脸识别 [J]. 光电工程,2014,41(12):66-71.
ZHANG Hongjie,WANG Xian,SUN Ziwen. Face Recognition Based on Shearlet Multi-orientation Adaptive Weighted Fusion and Sparse Representation [J]. Opto-Electronic Engineering,2014,41(12):66-71.

【9】ZHANG Baohua,LU Xiaoqi,PEI Haiquan,et al. A fusion algorithm for infrared and visible images based on saliency analysis and non-subsampled Shearlet transform [J]. Infrared Physics & Technology(S1350-4495),2015,73(11):286-297.

【10】郑伟,孙雪青,郝冬梅,等. Shearlet 变换和稀疏表示相结合的甲状腺图像融合 [J]. 光电工程,2015,42(1):77-83.
ZHENG Wei,SUN Xueqing,HAO Dongmei,et al. Thyroid Image Fusion Based on Shearlet Transform and Sparse Representation [J]. Opto-Electronic Engineering,2015,42(1):77-83.

【11】Singh Sneha,Gupta Deep,Anand R S,et al. Nonsubsampled shearlet based CT and MR medical image fusion using biologically inspired spiking neural network [J]. Biomedical Signal Processing and Control(S1746-8094),2015,18:91-101.

【12】WANG Zhishe,YANG Fengbao,PENG Zhihao,et al. Multi-sensor image enhanced fusion algorithm based on NSST and top-hat transformation [J]. Optik-International Journal for Light and Electron Optics(S0030-4026),2015,126:4184-4190.

【13】Anoop Suraj A,Francis Mathew,Kavya T S,et al. Discrete wavelet transform based image fusion and de-noising in FPGA [J]. Journal of Electrical Systems and Information Technology(S2314-7172),2014,3(1):72-81.

【14】张惊雷,赵俄英. 基于NSCT 的红外与可见光图像融合方法 [J]. 激光与红外,2013,43(3):319-322.
ZHANG Jinglei,ZHAO E′ying. Fusion method for infrared and visible light images based on NSCT [J]. Laser & Infrared, 2013,43(3):319-322.

【15】LI Xun,QIN Shiyin. Efficient fusion for infrared and visible images based on compressive sensing principle [J]. IET Image Process(S1751-9659),2011,5(2):141-147.

【16】WANG Zhou,Bovik A C,Sheikh H R,et al. Image quality assessment:From error visibility to structural similarity [J]. IEEE Transactions on Image Processing(S1057-7149),2004,13(4):600-612.

【17】HU Liangmei,GAO Jun,HE Kefeng. Research on quality measures for image fusion [J]. Acta Electronica Sinica (S0372-2112),2004,32(12 A):218-221.

【18】Piella G. New quality measures for image fusion [C]// Proceedings of the Seventh International Conference on Information Fusion,Stockholm,Sweden,June 28-July 1,2004:542-546.

【19】LI Chen′ou,Patrick Chong,Ronnier Luo M,et al. Additivity of colour harmony [J]. Color Research & Application (S0361-2317),2011,36(5):355-372.

引用该论文

WU Yanyan,WANG Yajie,SHI Xiangbin,WANG Linlin. Color Night Vision Method Combining NSST with Color Contrast Enhancement[J]. Opto-Electronic Engineering, 2016, 43(11): 88-94

吴燕燕,王亚杰,石祥滨,王琳霖. 结合NSST和颜色对比度增强的彩色夜视方法[J]. 光电工程, 2016, 43(11): 88-94

被引情况

【1】杨俊,赵林. 基于多特征检测与支持向量回归的图像文本提取算法. 光学技术, 2018, 44(5): 609-616

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