Tracking technology of moving target in foggy weather based on multi-wavelet enhancement

Zhang Su; Xu Chunyun; Wang Wensheng

Joint transform correlator(JTC) was applied to track the moving target in foggy weather or the other low visibility environment, to solve the low recognition ratio problem caused by low contrast and low visibility characteristic of the target and the background noise interference in this environment, a pre-processing method based on multi-wavelet enhancement was applied, it can use different methods to process the high and low frequency coefficients according to the different feathers of the decomposition coefficients on the basis of the multi-wavelet transform merits, which can make the processed image undistorted, simultaneously enhance the contrast and the target edge, and suppress the background noise. The optical correlation experiments on a large number of moving targets captured in a simulation fog environment show that this method can effectively enhance the efficiency of the moving target tracking in foggy weather environment and verify the feasibility of this algorithm.

1. Laboratory of Contemporary Optical Measure Technology,Changchun University of Science and Technology,Changchun 130022,China

Received Date: 2013-06-05

Rev Recd Date: 2013-07-03

Publish Date: 2014-02-25

Key words:

Abstract: Joint transform correlator(JTC) was applied to track the moving target in foggy weather or the other low visibility environment, to solve the low recognition ratio problem caused by low contrast and low visibility characteristic of the target and the background noise interference in this environment, a pre-processing method based on multi-wavelet enhancement was applied, it can use different methods to process the high and low frequency coefficients according to the different feathers of the decomposition coefficients on the basis of the multi-wavelet transform merits, which can make the processed image undistorted, simultaneously enhance the contrast and the target edge, and suppress the background noise. The optical correlation experiments on a large number of moving targets captured in a simulation fog environment show that this method can effectively enhance the efficiency of the moving target tracking in foggy weather environment and verify the feasibility of this algorithm.

HTML

Reference (37)

[1]	Kamal H A, Cherri A K. Complementary-reference and complementary-scene for real-time fingerprint verification using joint transform correlator[J]. Optics Laser Technology, 2009, 41(2009): 643-650.
[2]
[3]	Miao Hua, Chen Yu, Wang Wensheng. Research on the application of reversing phase technology in joint transform correlator[J]. Infrared and Laser Engineering, 2007, 36(s): 190-192. (in Chinese)
[4]
[5]	Liu Wenzhe, Zhang Wanyi, Dong Hui, et al. Study on infrared target recognition algorithm with optical correlation [J]. Chinese Journal of Scientific Instrument, 2011, 32(4): 850-855. (in Chinese)
[6]	苗华, 陈宇, 王文生. 提高复杂背景目标探测与识别能力的研究[J]. 红外与激光工程, 2007, 36(s): 190-192.
[7]
[8]	Zhang Qibo, Wang Youjian, Zhang Su, et al. Recognition technology of low light level target based on optical correlation[J]. Journal of Test and Measurement Technology, 2012, 26(S): 66-70. (in Chinese)
[9]
[10]	Chen Fanghan, Wang Wensheng. Target recognition in clutter scene based on wavelet transform[J]. Optics Communications, 2009, 282(2009): 523-526. (in Chinese)
[11]	Gonzales R C, Woods R E, Eddins S L. Digital Image Processing Using MATLAB[M]. Beijing: Publishing House of Electronics Industry, 2005: 54-101.
[12]	刘文哲, 张婉怡, 董会, 等. 光学相关红外目标识别算法研究[J]. 仪器仪表学报, 2011, 32(4): 850-855.
[13]
[14]	Li Guosong, Meng Weihua. Target edge searching segmentation method based on wavelet transform[J]. Infrared and Laser Engineering, 2009, 38(1): 185-188. (in Chinese)
[15]	Luo Xiaoqing, Wu Xiaojun. Detection algorithm for infrared small and weak targets based on wavelet transform and Gabor filter[J]. Infrared and Laser Engineering, 2011, 40(9): 1818-1822. (in Chinese)
[16]
[17]	Chen Suting, Wu Qinzhang. Image de-noising method based on multi-wavelet transform and synthesis[J]. Infrared and Laser Engineering, 2007, 36(1): 139-142. (in Chinese)
[18]	张淇博, 王友健, 张肃, 等. 基于光学相关的微光目标识别技术 [J]. 测试技术学报, 2012, 26(S): 66-70.
[19]
[20]	Dong Weijun, Zhou Mingquan, Geng Guohua. New image enhancement method based on multi-wavelet transform[J]. Journal of Chinese Computer System, 2007, 28(7): 1259-1261. (in Chinese)
[21]
[22]	Cheng Lizhi, Wang Hongxia, Luo Yong. Theory and Application of Wavelet[M]. Beijing: Science Press, 2005: 280-282. (in Chinese)
[23]
[24]
[25]	李国嵩, 孟卫华. 基于小波变换的目标边缘搜索分割方法 [J]. 红外与激光工程, 2009, 38(1): 185-188.
[26]
[27]
[28]	罗晓清, 吴小俊. 利用小波变换与Gabor滤波检测红外小目标[J]. 红外与激光工程, 2011, 40(9): 1818-1822.
[29]
[30]
[31]	陈苏婷, 吴钦章. 基于多小波变换及综合阈值的图像去噪方法[J]. 红外与激光工程, 2007, 36(1): 139-142.
[32]
[33]
[34]	董卫军, 周明全, 耿国华. 一种新的基于多小波变换的图像增强方法[J]. 小型微型计算机系统, 2007, 28(7): 1259-1261.
[35]
[36]
[37]	成礼智, 王红霞, 罗永. 小波的理论与应用[M]. 北京: 科学出版社, 2005: 280-282.

Tracking technology of moving target in foggy weather based on multi-wavelet enhancement

Abstract

References

Proportional views

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Related

Proportional views