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Noise is an important factor affecting the image quality of laser coherent field high resolution imaging system. And there exists not only background light additive noise but also laser multiplicative speckle noise in a laser coherent field imaging system. Both of the above noise affect the imaging quality of laser coherent field system. In order to improve the imaging quality from the perspective of noise suppression and settle the imaging quality degradation problem of laser multiplicative speckle noise and background additive noise in the laser coherent field imaging system, the model for the influence of multiplicative speckle noise and background additive noise on laser echo field demodulated signal is established in atmospheric downlink. Then, based on the model, a novel homomorphic filter and sparse matrix trace cascade compound de-noising algorithm is put forward. Firstly, based on the homomorphic filtering theory, the laser multiplicative speckle noise in the laser echo demodulated signal is converted into the additive noise by logarithmic transformation. Then the low-frequency laser multiplicative speckle noise is filtered by the high-pass filter, and the high-frequency demodulated signal is retained. The logarithmic inverse transform is used to obtain the laser echo demodulation signal after the multiplicative speckle noise has been filtered out. Next, the phase random disturbance of atmosphere in laser echo demodulated signal is suppressed by phase closure technology and the imaging spectrum component is reconstructed by the spectrum iterative reconstruction method. Then the high resolution image is obtained by spectrum component inverse Fourier transform. Finally, the effect of background additive noise on the image quality is suppressed by the sparse base tracking theory. The simulated and outdoor experiment result are used to verify the denoising effect and image quality enhancement effect of the composite de-noising method. Compared with the existing single denoising method, the composite denoising method is shown to be able to effectively eliminate laser multiplicative speckle noise and background additive noise at one time. The proposed method can improve image contrast and promote the Strehl ratio of imaging quality in a coherent imaging system. It provides a theoretical basis for improving imaging quality and denosing laser multiplicative speckle noise and background additive noise in coherent field imaging system.
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Keywords:
- laser speckle noise /
- background light noise /
- homomorphic filter /
- sparse denoising
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Google Scholar
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Cheng Z Y 2015 Ph.D. Dissertation (Xi’an: Chinese Academy Sciences University) (in Chinese)
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图 1 激光相干场成像原理示意图
Figure 1. Schematic diagram of laser coherent field imaging.
图 2 激光相干场成像信号去噪信息流程图
Figure 2. Flow chart of denoising information for laser coherent field imaging signal.
图 3 相位闭合示意图
Figure 3. Schematic diagram of phase closure technique.
图 4 不同算法去噪效果图 (a)原始模板图像; (b)由图像算法直接重构未去噪的图像; (c)由稀疏去噪算法去加性噪声后得到的图像; (d)由同态滤波去乘性散斑噪声后得到的图像; (e)由同态滤波和稀疏复合去噪后得到的图像
Figure 4. Denoising effect diagram of different algorithms: (a) Original template image; (b) direct reconstruction of undenoised images by image algorithms; (c) image obtained by sparse denoising algorithm after additive noise removal; (d) image obtained by removing multiplicative speckle noise by homomorphic filtering; (e) image obtained by homomorphic filtering and sparse combined denoising.
图 5 室外成像去噪实验效果对比图 (a) 室外成像目标; (b)直接重构成像; (c)去噪后重构成像
Figure 5. Comparison of outdoor imaging de-noising experiment: (a) Ooutdoor imaging target; (b) direct reconstruction imaging; (c) reconstruction imaging after de-noising.
表 1 不同去噪方法指标对比表
Table 1. Comparison indicators table of different de-noising methods.
对比项 直接重建法 稀疏去噪法 同态滤波法 复合去噪法 斯特列尔比 46.3% 50.1% 52.7% 63.5% 图像对比度 0.25 0.27 0.42 0.46 平均梯度 5.98 6.11 6.28 7.13 
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[1] 朱曼曼, 时东锋, 胡顺星, 王英俭 2017 量子电子学报 34 145
Zhu M M, Shi D F, Hu S S, Wang Y J 2017 Chinese Journal of Quantum Electronics 34 145
[2] 邓慧, 张蓉竹, 孙年春 2016 应用光学 36 0129002
Deng H, Zhang R Z, Sun N C 2016 Journal of Applied Optics 36 0129002
[3] 陈艳, 李中梁, 南楠, 步扬, 王瑄, 潘柳华, 王向朝 2015 光学学报 38 0811004
Chen Y, Li Z L, Nan N, Bu Y, Wang X, Pan L H, Wang X C 2015 Acta Optic. Sin. 38 0811004
[4] 吴育民, 段海燕, 文永富, 程灏波, 王谭 2018 影像科学与光化学 36 187
Google Scholar
Wu Y M, Duan H Y, Wen Y F, Cheng H B, Wang T 2018 Imaging Science and Photochemistry 36 187
Google Scholar
[5] 杨鹏程, 刘洋, 朱新栋, 胥光申, 肖渊 2017 应用光学 38 221
Yang P C, Liu Y, Zhu X D, Xu G S, Xiao Y 2017 Journal of Applied Optics 38 221
[6] 陈波, 杨靖, 杨旭, 李小阳 2015 中国激光 42 1012002
Chen B, Yang J, Yang X, Li X Y 2015 Chinese Journal of Lasers 42 1012002
[7] 袁治灵, 陈俊波, 黄伟源, 魏波, 唐志列 2018 光学学报 38 0511002
Yuan Z L, Chen J B, Huang W Y, Wei B, Tang Z L 2018 Acta Optical Sinica 38 0511002
[8] 王大勇, 王云新, 郭莎, 戎路, 张亦卓 2014 63 154205
Google Scholar
Wang D Y, Wang Y X, Guo S, Rong L, Zhang Y Z 2014 Acta Phys. Sin. 63 154205
Google Scholar
[9] 田小平, 程新, 吴成茂, 刘一博 2015 西安邮电大学学报 20 51
Tian X P, Cheng X, Wu C M, Liu Y B 2015 Journal of Xi’an University of Posts and Telecommunications. 20 51
[10] Kuechel M US Patent 6 804 011 [2004-10-12]
[11] Yu H C, Gao J L, Li A T 2016 Opt. Lett. 41 994
Google Scholar
[12] 张艳艳, 陈苏婷, 葛俊祥, 万发雨, 梅永, 周晓彦 2017 66 129501
Google Scholar
Zhang Y Y, Chen S T, Ge J X, Wan F Y, Mei Y, Zhou X Y 2017 Acta Phys. Sin. 66 129501
Google Scholar
[13] 陈晔曜, 蒋刚毅, 邵华, 姜浩, 郁梅 2018 光电工程 45 180083
Google Scholar
Chen Y Y, Jiang G Y, Shao H, Jian H, Yu M 2018 Opto-Electronic Engineering 45 180083
Google Scholar
[14] Chiang J C, Kao P H, Chen Y S, et al. 2017 Circ. Syst. Signal Pr. 36 2786
Google Scholar
[15] Zhang K, Zuo W, Chen Y, Meng D, Zhang L 2017 IEEE Trans. Image Process. 26 3142
Google Scholar
[16] 郝红星, 吴玲达, 宋晓瑞 2018 计算机学报 41 1
Google Scholar
Hao H X, Wu L D, Song X R 2018 Chienese Journal of Computers 41 1
Google Scholar
[17] 沈晨, 张旻 2018 探测与控制学报 40 128
Shen C, Zhang M 2018 Journal of Detection & Control 40 128
[18] 詹曙, 王俊, 杨福猛, 方琪 2015 电子学报 43 523
Google Scholar
Zhan S, Wang J, Yang F M, Fang Q 2015 Acta Electronic Sinica 43 523
Google Scholar
[19] Mairal J, Bach F, Ponce J 2012 IEEE Transactions on Pattern Analysis and Machine Intelligence 34 791
Google Scholar
[20] 程志远, 马彩文, 罗秀娟, 张羽, 朱香平, 夏爱利 2015 64 124203
Google Scholar
Cheng Z Y, Ma C W, Luo X J, Zhang Y, Zhu X P, Xia A L 2015 Acta Phys. Sin. 64 124203
Google Scholar
[21] 程志远, 马彩文, 马青 2017 66 244202
Google Scholar
Cheng Z Y, Ma C W, Ma Q 2017 Acta Phys. Sin. 66 244202
Google Scholar
[22] Rhodes W T 2012 Appl. Opt. 51 A11
[23] 程志远 2015 博士学位论文(西安: 中国科学院大学)
Cheng Z Y 2015 Ph.D. Dissertation (Xi’an: Chinese Academy Sciences University) (in Chinese)
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