小波阈值降噪算法在光电探测器信号处理中的应用

吴艳; 张蓉竹

doi:doi:10.3788/gzxb20194810.1004004

光子学报, 2019, 48 (10): 1004004, 网络出版: 2019-11-14

小波阈值降噪算法在光电探测器信号处理中的应用

Application of Wavelet Threshold Denoising Algorithm in Photodetector Signal Processing

论文大纲

吴艳 ^*张蓉竹

作者单位

四川大学电子信息学院,成都 610064

光电探测器小波阈值降噪分层阈值阈值函数信噪比均方误差 Photodetector Wavelet threshold denoising Hierarchical thresholds Threshold function SNR MSE

摘要

针对光电探测器传统降噪处理中软、硬阈值函数存在的缺点,提出了一种含参数的阈值函数和逐层变化的阈值相结合的小波阈值降噪算法.该算法可以调整参数使生成的阈值函数于软、硬阈值函数之间,且在临界阈值处平滑过渡,保留部分有用信号.应用过程中阈值可随着分解层数的改变而改变,对各个分解层有自适应特征,减少小波系数阈值处理中的固定偏差,从而在保留原有信号的同时减除不必要噪声.仿真及实测结果表明,采用该小波阈值降噪算法处理的信号信噪比较高、均方误差较小,有效地抑制噪声对光电探测器输出信号的干扰.

Abstract

To overcome the shortcomings of the traditional noise reduction processing in photodetectors, a novel wavelet threshold denoising algorithm is presented. A threshold function with parameters and layer-by-layer threshold are combined in the algorithm. By adjusting the parameters, a threshold function can be generated, which value is between soft and hard threshold functions, and can realize the smooth transition at the critical threshold. During the application, the threshold can be changed with the change of decomposition layers. The individual decomposition layer has adaptive characteristics. So it can reduce the fixed deviation in the wavelet threshold processing, and then the unnecessary noise can be restrained while the original signal is remained. The results of simulation and experiment show that the SNR of signal processed by the wavelet threshold denoising algorithm are relatively high and the mean square error is small. Furthermore, the algorithm can effectively suppress the interference of noise on the output signal of photodetector.

参考文献

[1] ZHAO Y, LI C, SHEN L. Recent research process on perovskite photodetectors: a review for photodetector-materials, physics, and applications［J］. Chinese Physics B, 2018, 27(12):127806.

[2] 王燕, 张锐. 光电探测器特性在TDLAS 气体检测中的影响［J］. 光学学报, 2016, 36(2):0230002.

WANG Yan,ZHANG Rui. Photo detector characteristics effect on TDLAS gas detection［J］. Acta Optica Sinica, 2016,36(2): 0230002.

[3] RAO G A, MAHULIKAR S P. New criterion for aircraft susceptibility to infrared guided missiles［J］.Aerospace Science & Technology, 2005, 9(8):701-712.

[4] 康宏向. 激光侦听信号中大气噪声与环境噪声的降噪研究［D］. 长沙：国防科学技术大学, 2003.

KANG Hong-xiang.Study on noise reduction of atmospheric noise and ambient noise in laser acoustic signal ［D］.Changsha: Master's Thesis of University of Defense Science and Technology,2003.

[5] GAO C, ZHOU S. Wavelet transform threshold noise reduction methods in the oil pipeline leakage monitoring and positioning system［J］.Journal of Electronics, 2010, 27(3):405-411.

[6] ZHAO R M, CUI H M. Improved threshold denoising method based on wavelet transform［C］. Proceedings of 2010 4th International Conference on Intelligent Information Technology Application(Volume 2), IEEE, 2010, 33: 1354-1359.

[7] DONOHO D L. Denoising by soft-thresholding［J］. IEEE Transactions on Information Theory, 1995, 41(3): 613-627.

[8] DONOHO D L, JOHNSTONE I M. Ideal spatial adaption via waveletshrinkage［J］. Biometrika, 1994, 81(3): 425-455.

[9] DONOHO D L. Orthonormal ridgelets and linear singularities［J］.Siam Journal on Mathematical Analysis, 2000, 31(5):1062-1099.

[10] 赵瑞珍, 宋国乡, 王红. 小波系数阈值估计的改进模型［J］. 西北工业大学学报, 2001, 19(4):626-628.

ZHAO Rui-zhen, SONG Guo-xiang, WANG Hong. Better threshold estimation of wavelet coefficients for improving denoising［J］.Jounal of Northwestern Polytechnical University, 2001,19(4):626-628.

[11] 彭其先, 马如超, 李泽仁, 等. 光电倍增管脉冲性能研究［J］. 光子学报, 2002, 31(5):620-623.

PENG Qi-xian, MA Ru-chao, LI Ze-ren, et al. Photomultiplier under pluse light［J］. Acta Photonica Sinica, 2002, 31(5):620-623.

[12] 袁正兵, 肖清泉, 杨文献,等. In0.53 Ga0.47 As/InP雪崩光电二极管响应及电学特性［J］. 光子学报,2018,47(3):0304002.

YUAN Zheng-bing, XIAO Qing-quan, YANG Wen-xian,et al. Response and electrical characteristics of In_(0.53)Ga_(0.47)As/InP avalanche photodiode［J］. Acta Photonica Sinica, 2018, 47(3):0304002.

[13] DEHLINGER G, KOESTER S J, SCHAUB J D,et al. High-speed germanium-on-SOI lateral PIN photodiodes［J］. IEEE Photonics Technology Letters, 2015, 16(11):2547-2549.

[14] LLOYD D R. What was measured in Millikan's study of the photoelectric effect［J］.American Journal of Physics, 2015, 83(9):765-772.

[15] 韩勇. 光电检测电路的噪声分析与处理［D］. 哈尔滨：哈尔滨工程大学, 2011.

HAN Yong. Analysisand processing of the noise in photoelectric detection circuit［D］. Harbin: Harbin Engineering University,2011.

[16] 闫振纲, 林颖璐, 杨娟, 等. 光电探测器随机噪声特征量统计分布函数［J］. 物理学报, 2012, 61(20):88-96.

YAN Z G, LIN Y L, YANG J, et al. The distribution functions of characteristic quantities for random noise signal of photodetector［J］. Acta Physica Sinica, 2012, 61(20):2021-2036.

[17] 江虹, 苏阳. 一种改进的小波阈值函数去噪方法［J］. 激光与红外, 2016,46(1):119-122.

JIANG Hong, SU Yang. Denoising method based on improved wavelet threshold function［J］.Laser and Infrared, 2016,46(1):119-122.

[18] 屈直, 张伯虎. 一种改进的小波阈值算法在激光侦听中的应用［J］. 激光技术, 2014, 38(2):218-224.

QU Zhi, ZHANG Bo-hu. An improved wavelet threshold algorithm applied in laser interception［J］.Laser Technology, 2014, 38(2):218-224.

吴艳, 张蓉竹. 小波阈值降噪算法在光电探测器信号处理中的应用[J]. 光子学报, 2019, 48(10): 1004004. WU Yan, ZHANG Rong-zhu. Application of Wavelet Threshold Denoising Algorithm in Photodetector Signal Processing[J]. ACTA PHOTONICA SINICA, 2019, 48(10): 1004004.

小波阈值降噪算法在光电探测器信号处理中的应用

关于本站 Cookie 的使用提示

全站搜索

小波阈值降噪算法在光电探测器信号处理中的应用

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索