基于局部关联信息的视频监控图像中γ辐射噪斑的消除方法

曹令; 刘桂华; 邓豪; 邓磊; 周炳宏

doi:10.7538/yzk.2021.youxian.0355

基于局部关联信息的视频监控图像中γ辐射噪斑的消除方法

西南科技大学信息工程学院,四川绵阳621000
西南科技大学特殊环境机器人技术四川省重点实验室,四川绵阳621000

计量
- 文章访问数: 73
- HTML全文浏览量: 0
- PDF下载量: 274
出版历程
- 刊出日期: 2022-07-19

Method for Eliminating γ Radiation Plaque Noise in Video Surveillance Image Based on Local Correlation Information

School of Information Engineering, Southwest University of Science and Technology, Mianyang 621000, China
Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Southwest University of Science and Technology, Mianyang 621000, China

摘要

摘要: 为消除γ辐射环境视频监控图像内大量形状不规则、分布无规律、能量不均衡的噪斑，提出一种利用图像局部相邻像素关联信息去除噪斑的方法。首先根据γ辐射环境视频监控图像噪斑像素值的突变特性分割噪斑区域，再利用噪斑与当前帧噪斑相邻干净区域的局部关联性及噪斑与相邻帧相同坐标干净区域像素点的局部关联性，以两个干净区域像素值为基准、像素值差值为关联度，采用步进式方法修复噪斑区域。实验结果表明，与传统的图像噪斑去除算法相比，本方法在量化指标和视觉感知上均有较大提高。该噪斑消除方法可有效去除γ辐射环境视频监控图像的噪斑，保留图像细节纹理信息。
- γ辐射环境 ,
- 噪斑分割 ,
- 局部关联信息 ,
- 图像修复
Abstract: In order to eliminate a lot of plaque noises with irregular shape, irregular distribution and unbalanced energy included in video surveillance image of γ radiation environment, a method was proposed to remove the plaque noise by using the correlation information of the local neighboring pixel of the image. Firstly, according to the characteristic of the plaque noise pixel value mutation in γ radiation environment video surveillance image, the plaque noise area was segmented. Then the plaque noise area was repaired by a stepbystep method with the pixel value of the two clean areas as the reference and with the pixel value difference as the correlation degree. In the procedure, a local correlation characteristic between a plaque noise area and neighboring clean area in the frame and another local correlation characteristic between the plaque noise area in the frame and the pixel of the same corridor clear area in the adjacent frame were used. The experiment results show that compared with the traditional image plaque noise removal algorithm, this method has a greater improvement in quantification indicator and visual perception. This noise removal method can effectively remove the plaque noise of γ radiation environment video surveillance image and retain the image detail information.
- γ radiation environment ,
- plaque noise segmentation ,
- local correlation information ,
- image restoration

HTML全文

参考文献(23)

[1]	李利娜，孙润军，陈美玉，等. 辐射防护材料的研究进展[J]. 合成纤维，2019，48(10)：21-25. LI Lina, SUN Runjun, CHEN Meiyu, et al. Research progress on radiation protection materials[J]. Synthetic Fiber in China, 2019, 48(10): 21-25(in Chinese).
[2]	王祖军，薛院院，马武英，等. 电离总剂量效应诱发PPD CMOS图像传感器性能退化的实验研究[C]∥中国核学会2017年学术年会论文集. 北京：原子能出版社，2017.
[3]	GOIFFON V, VIRMONTOIS C, MAGNAN P, et al. Identification of radiation induced dark current sources in pinned photodiode CMOS image sensors[J]. IEEE Transactions on Nuclear Science, 2012, 59(4): 918-926.
[4]	RAO P R, WANG X Y, THEUWISSEN A J P. Degradation of CMOS image sensors in deepsubmicron technology due to γ-irradiation[J]. Solid State Electronics, 2008, 52(9): 1407-1413.
[5]	BULENT B. Preparation and characterization of ironoreimbedded silicone rubber materials for radiation protection[J]. Nuclear Science and Techniques, 2018, 29(9): 42-47.
[6]	赵磊，尚钰轩，袁爽，等. 载人深空探索中空间辐射防护技术的研究进展[J]. 科学通报，2019，64(20)：2087-2103. ZHAO Lei, SHANG Yuxuan, YUAN Shuang, et al. Research progress of space radiation protection technologies in manned deep space exploration missions[J]. Chinese Science Bulletin, 2019, 64(20): 2087-2103(in Chinese).
[7]	王桂珍，林东生，齐超，等. 0.18 μm CMOS电路瞬时剂量率效应实验研究[J]. 原子能科学技术，2014，48(11)：2165-2169. WANG Guizhen, LIN Dongsheng, QI Chao, et al. Experimental research of transient does rate effect on CMOS circuit with feature size of 0.18 μm[J]. Atomic Energy Science and Technology, 2014, 48(11): 2165-2169(in Chinese).
[8]	王祖军，唐本奇，肖志刚，等. CCD辐射损伤效应及加固技术研究进展[J]. 半导体光电，2009，30(6)：797-802，814. WANG Zujun, TANG Benqi, XIAO Zhigang, et al. Progress of radiation damage effects and hardening technology on CDD[J]. Semiconductor Optoelectronics, 2009, 30(6): 797-802, 814(in Chinese).
[9]	王姮，桑瑞娟，张华. 一种强辐射场景监测下图像降噪的新方法[J]. 传感器与微系统，2011，30(11)：59-61. WANG Heng, SANG Ruijuan, ZHANG Hua. A new image denoising method for monitoring in intense radioactive environment[J]. Transducer and Microsystem Technologies, 2011, 30(11): 5961(in Chinese).
[10]	杨斌，赵立宏，邓骞. 基于图像修复技术的抗核辐射图像恢复方法[J]. 南华大学学报(自然科学版)，2016，30(4)：56-61. YANG Bin, ZHAO Lihong, DENG Qian. A novel antinuclear radiation image restoration algorithm based on inpainting technology[J]. Journal of University of South China (Science and Technology), 2016, 30(4): 56-61(in Chinese).
[11]	陈明举. 基于稀疏表示与变分法的核辐射干扰图像增强技术研究[D]. 绵阳：西南科技大学，2020.
[12]	SUN Xin, LUO Hongwei, LIU Guihua, et al. Lightweight image restoration network for strong noise removal in nuclear radiation scenes[J]. Sensors, 2021, 21(5): 1810-1810.
[13]	YU Yongjian, ACTON S T. Speckle reducing anisotropic diffusion[J]. IEEE Transactions on Image Processing, 2002, 11(11): 1262-1270.
[14]	BUADES A, COLL B, MOREL J M. Nonlocal means denoising[J]. Image Processing on Line, 2011, 1: 208-212.
[15]	DABOV K, FOI A, KATKOVNIK V, et al. Image denoising by sparse 3D transformdomain collaborative filtering[J]. IEEE Transactions on Image Processing, 2007, 16(8): 2080-2095.
[16]	GU Shuhang, ZHANG Lei, ZUO Wangmeng, et al. Weighted nuclear norm minimization with application to image denoising[C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition. US: IEEE, 2014.
[17]	TREECE G. Morphologybased noise reduction: Structural variation and thresholding in the bitonic filter[J]. IEEE Transactions on Image Processing, 2019, 29: 336-350.
[18]	张文仲. 电离辐射粒子在人体组织中能量沉积的微剂量学研究[D]. 北京：中国人民解放军军事医学科学院，2003.
[19]	郑然，刘超，刘晗，等. 辐射环境下CMOS图像传感器的暗电流幅值分布预测方法[J]. 微电子学与计算机，2018，35(4)：144-148. ZHENG Ran, LIU Chao, LIU Han, et al. Methods for prediction darkcurrent distribution of CMOS image sensor in radiation environment[J]. Microelectronics & Computer, 2018, 35(4): 144-148(in Chinese).
[20]	李鹏伟，郭旗，任迪远，等. 电荷耦合器件的60Co γ射线辐照损伤退火效应[J]. 原子能科学技术，2010，44(5)：603-607. LI Pengwei, GUO Qi, REN Diyuan, et al. Annealing effects of charge coupled devices after 60Co γ irradiation[J]. Atomic Energy Science and Technology, 2010, 44(5): 603-607(in Chinese).
[21]	李豫东，郭旗，陆妩，等. CCD在不同注量率电子辐照下的辐射效应研究[J]. 原子能科学技术，2012，46(3)：346-350. LI Yudong, GUO Qi, LU Wu, et al. Research on electron irradiation damage effects of charge coupled device[J]. Atomic Energy Science and Technology, 2012, 46(3): 346-350(in Chinese).
[22]	徐守龙，邹树梁，黄有骏，等. CCD与CMOS像素传感器γ射线电离辐射响应特性对比研究[J]. 发光学报，2018，39(6)：815-822. XU Shoulong, ZOU Shuliang, HUANG Youjun, et al. Comparative study on γ-ray radiation response characteristics of CCD and CMOS pixel sensor[J]. Chinese Journal of Luminescence, 2018, 39(6): 815-822(in Chinese).
[23]	ABDELHAMED A, LIN S, BROWN M S. A highquality denoising dataset for smartphone cameras[C]∥CVF Conference on Computer Vision & Pattern Recognition. US: IEEE, 2018.

施引文献

资源附件(0)

计量

文章访问数: 73
HTML全文浏览量: 0
PDF下载量: 274
被引次数: 0

基于局部关联信息的视频监控图像中γ辐射噪斑的消除方法

计量

出版历程

Method for Eliminating γ Radiation Plaque Noise in Video Surveillance Image Based on Local Correlation Information

计量

出版历程

目录