Improved BM3D method for flash X-ray radiograph denoising

Wei Caihua; Tang Zhipeng; Jing Yuefeng; Guan Yonghong; Liu Jin

doi:10.11884/HPLPB202436.240217

Volume 36 Issue 10

Oct. 2024

Turn off MathJax

Article Contents

Article Navigation > High Power Laser and Particle Beams > 2024 > 36(10): 104002

Wei Caihua, Tang Zhipeng, Jing Yuefeng, et al. Improved BM3D method for flash X-ray radiograph denoising[J]. High Power Laser and Particle Beams, 2024, 36: 104002. doi: 10.11884/HPLPB202436.240217

Citation:

Wei Caihua, Tang Zhipeng, Jing Yuefeng, et al. Improved BM3D method for flash X-ray radiograph denoising[J]. High Power Laser and Particle Beams, 2024, 36: 104002. doi: 10.11884/HPLPB202436.240217

Wei Caihua, Tang Zhipeng, Jing Yuefeng, et al. Improved BM3D method for flash X-ray radiograph denoising[J]. High Power Laser and Particle Beams, 2024, 36: 104002. doi: 10.11884/HPLPB202436.240217

Citation:

Wei Caihua, Tang Zhipeng, Jing Yuefeng, et al. Improved BM3D method for flash X-ray radiograph denoising[J]. High Power Laser and Particle Beams, 2024, 36: 104002. doi: 10.11884/HPLPB202436.240217

PDF( 2900 KB)

Improved BM3D method for flash X-ray radiograph denoising

doi: 10.11884/HPLPB202436.240217

Institute of Fluid Physics, CAEP, Mianyang 621900, China

Received Date: 2024-06-30
Accepted Date: 2024-09-15
Rev Recd Date: 2024-09-15

Available Online: 2024-09-24

Publish Date: 2024-10-15

Abstract

Abstract

Gaussian noise is the main noise in flash X-ray radiographs, which will be magnified in the subsequent density inversion and other processing, and seriously affect the results of density reconstruction and object boundary extraction. Therefore, eliminating Gaussian noise is the key content of flash X-ray radiograph denoising research. According to the characteristics of image noise in flash X-ray radiographs and the rotational symmetry of object axes, this paper studies the denoising algorithm of flash X-ray radiographs based on BM3D (Block Matching and 3D Filtering). To overcome the defect that it is difficult to obtain high-quality similar blocks in flash X-ray radiographs, the image sources for providing similar blocks are increased by rotating and mirroring the noisy degraded images without destroying the noise independence. At the same time, by introducing grayscale transformation of image blocks, the grayscale value requirements in the original similarity requirements are reduced, the shape similarity requirements are improved, and the ability to obtain high-quality similar blocks is increased. Image denoising results show that the improved BM3D method in this paper achieves better denoising effect because the quality of similar blocks is guaranteed.
- flash X-ray radiograph,
- Gaussian noise,
- BM3D,
- denoising

FullText(HTML)

References(15)

References

[1]	Aufderheide III M B, Martz H E Jr, Slone D M, et al. Concluding report: quantitative tomography simulations and reconstruction algorithms[R]. UCRL-ID-146938, 2002: 1-19.
[2]	Clark D A, Espinoza C J. Proton radiography[R]. Physics Division Progress Report, 1999-2000: 156-168.
[3]	危才华, 景越峰, 张小琳, 等. 基于极大似然模型和期望最大化算法的闪光图像重建[J]. 强激光与粒子束, 2016, 28:054003 doi: 10.11884/HPLPB201628.054003 Wei Caihua, Jing Yuefeng, Zhang Xiaolin, et al. Image reconstruction algorithm based on maximum likelihood-expectation maximum for radiography[J]. High Power Laser and Particle Beams, 2016, 28: 054003 doi: 10.11884/HPLPB201628.054003
[4]	景越峰, 管永红, 刘军. 基于改进开关中值滤波的多孔网栅图像脉冲噪声消除[J]. 强激光与粒子束, 2015, 27:084006 doi: 10.11884/HPLPB201527.084006 Jing Yuefeng, Guan Yonghong, Liu Jun. Removal of impulse noise of anti-scatter grided images with modified switching median filters[J]. High Power Laser and Particle Beams, 2015, 27: 084006 doi: 10.11884/HPLPB201527.084006
[5]	Meng Yizhen, Zhang Jun. A novel gray image denoising method using convolutional neural network[J]. IEEE Access, 2022, 10: 49657-49676. doi: 10.1109/ACCESS.2022.3169131
[6]	Holla K S, Park N, Lee B. EFID: edge-focused image denoising using a convolutional neural network[J]. IEEE Access, 2023, 11: 9613-9626. doi: 10.1109/ACCESS.2023.3239835
[7]	谷学静, 杨宝上, 刘秋月. 基于高斯滤波和AKAZE-LATCH的图像匹配算法[J]. 半导体光电, 2023, 44(4):639-644 Gu Xuejing, Yang Baoshang, Liu Qiuyue. Image matching algorithm based on Gaussian filtering and AKAZE-LATCH[J]. Semiconductor Optoelectronics, 2023, 44(4): 639-644
[8]	李文娟, 陈军, 张永刚, 等. 基于改进加权均值滤波的医学影像图像除噪研究[J]. 辽宁大学学报(自然科学版), 2022, 49(1):30-35 Li Wenjuan, Chen Jun, Zhang Yonggang, et al. Research of medical image denoising based on improved weighted mean filtering[J]. Journal of Liaoning University (Natural Sciences Edition), 2022, 49(1): 30-35
[9]	肖丹, 黄玉清. 改进的各向异性扩散图像去噪算法[J]. 自动化仪表, 2017, 38(7):1-3 Xiao Dan, Huang Yuqing. Improved anisotropic diffusion image denoising algorithm[J]. Process Automation Instrumentation, 2017, 38(7): 1-3
[10]	Buades A, Coll B, Morel J M. A review of image denoising algorithms, with a new one[J]. Multiscale Modeling & Simulation, 2005, 4(2): 490-530.
[11]	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. doi: 10.1109/TIP.2007.901238
[12]	俞汪涛, 许鹏, 鲍杰, 等. 基于BM3D算法的快中子图像降噪方法[J]. 核电子学与探测技术, 2023, 43(2):369-375 doi: 10.3969/j.issn.0258-0934.2023.02.025 Yu Wangtao, Xu Peng, Bao Jie, et al. Fast neutron image denoising method based on BM3D algorithm[J]. Nuclear Electronics & Detection Technology, 2023, 43(2): 369-375 doi: 10.3969/j.issn.0258-0934.2023.02.025
[13]	唐艳, 潘伟, 张利, 等. 基于BM3D去噪算法在天文图像中的应用[J]. 智能计算机与应用, 2022, 12(9):193-197 doi: 10.3969/j.issn.2095-2163.2022.09.035 Tang Yan, Pan Wei, Zhang Li, et al. Application of BM3D denoising algorithm in astronomical images[J]. Intelligent Computer and Applications, 2022, 12(9): 193-197 doi: 10.3969/j.issn.2095-2163.2022.09.035
[14]	张小琳, 景越峰, 刘军. 基于Facet模型的闪光图像边缘检测[J]. 强激光与粒子束, 2010, 22(7):1640-1644 doi: 10.3788/HPLPB20102207.1640 Zhang Xiaolin, Jing Yuefeng, Liu Jun. Edge detection method based on Facet model for flash X-ray radiographs[J]. High Power Laser and Particle Beams, 2010, 22(7): 1640-1644 doi: 10.3788/HPLPB20102207.1640
[15]	Huynh-Thu Q, Ghanbari M. Scope of validity of PSNR in image/Video quality assessment[J]. Electronics Letters, 2008, 44(13): 800-801. doi: 10.1049/el:20080522