|
|
|
|
|
|
An Interpolation Method for Raman Imaging Using Voigt Function |
FAN Xian-guang1, 2, HUANG Yan-rui1, LIU Long1, XU Ying-jie1, WANG Xin1, 2* |
1. Department of Instrumental and Electrical Engineering, School of Aerospace Engineering, Xiamen University, Xiamen 361005, China
2. Fujian Key Laboratory of Universities and Colleges for Transducer Technology, Xiamen 361005, China
|
|
|
Abstract Raman imaging is a very important part of Raman spectroscopy technology. By generating pseudo-color images of spectral data, a substance component’s concentration and location distribution information in the collected area can be obtained. At present, Raman imaging technology has gradually become one of the optimal solutions for monitoring biological activity and substance components. In order to obtain a clear imaging effect, the amount of data in the collection process should not be too small otherwise, the imaging effect is poor, the serrations are heavy, and the visual effect is not good. However, although the increase in the amount of data can get a better imaging effect, it will increase the time cost and reduce the instrument’s life. Therefore, it is of great significance to improve the spatial resolution of the imaging and reduce the temporal resolution of the imaging by interpolating the data of the collection points without increasing the time and hardware cost. In this paper, an image interpolation algorithm based on the study of the physical properties of Raman spectral waveform structure is proposed. Different from traditional image interpolation algorithm of image pixel values only for processing, by combining the Raman signal of physical properties, least square method and physical properties of the most suitable mathematical model of the Raman spectral peaks Voigt function of existing mathematical fitting spectrum data are extracted eigenvalue, and the extracted eigenvalue by linear interpolation method to calculate the unknown interpolation point. The spatial resolution of existing Raman images can be directly improved by calculating the Voigt function of interpolation points based on the eigenvalue of the GT function. Meanwhile, the scanning time can also be shortened, and the temporal resolution of Raman images can be improved by this method. At the same time, in order to verify the effectiveness and feasibility of the proposed algorithm, the original Raman images of a drug and a biological cell were interpolated, and the histogram Euclidean distance algorithm and structural similarity algorithm (SSIM, an authority image similarity evaluation algorithm) were used to evaluate the interpolation effect. The experimental results show that the proposed algorithm can preserve important information such as the distribution and concentration of sample components well when the pixel increment is 50% and 75% respectively. The proposed algorithm can improve the performance of Raman imaging without upgrading the hardware and is recommended as an effective supplement to the data processing and software of Raman imaging.
|
Received: 2021-04-12
Accepted: 2021-06-09
|
|
Corresponding Authors:
WANG Xin
E-mail: xinwang@xmu.edu.cn
|
|
[1] Syed A, Smith E A. Annual Review of Analytical Chemistry, 2017, 10: 271.
[2] Qin J, Kim M S, Chao K, et al. Journal of Biosystems Engineering, 2017, 42(3): 170.
[3] Langer J, de Aberasturi D J, Aizpurua J, et al. ACS Nano, 2020, 14(1): 28.
[4] Rzhevskii A. Biosensors-Basel, 2019, 9(1): 25.
[5] Paudel A, Raijada D, Rantanen J. Adv. Drug. Deliv. Rev., 2015, 89: 3.
[6] Esmonde-White K A, Cuellar M, Uerpmann C, et al. Anal. Bioanal. Chem., 2017, 409(3): 637.
[7] He H R, Sun D W, Pu H B, et al. Crit. Rev. Food Sci. Nutr., 2019, 59(5): 770.
[8] Wang X, Liu G, Xu M, et al. Anal. Chem., 2019, 91(20): 12909.
[9] Yang G, Dai J, Liu X, et al. Applied Spectroscopy, 2020, 74(12): 1443.
[10] Ahlinder L, Lindstrom S W, Lejon C, et al. Nanomaterials, 2016, 6(5): 83.
[11] Cho S, Chung H. Anal. Sci., 2003, 19(9): 1327.
[12] XI Yang, LI Yue-e(席 杨, 李月娥). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2020, 40(2): 410.
[13] Zhou R G, Tan C Y, Fan P. Mod. Phys. Lett. B, 2017, 31(17): 1750184.
[14] Miao Y, Song D L, Shi W L, et al. 2nd International Conference on Computer Science and Application Engineering, 2018.
[15] Liu D H, Chen X H, Peng D. Int. J. Intell. Syst., 2019, 34(7): 1572.
|
[1] |
ZHU Wen-jing1, 2,FENG Zhan-kang1, 2,DAI Shi-yuan1, 2,ZHANG Ping-ping3,JI Wen4,WANG Ai-chen1, 2,WEI Xin-hua1, 2*. Multi-Feature Fusion Detection of Wheat Lodging Information Based on UAV Multispectral Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 197-206. |
[2] |
CHENG Xiao-xiang1, WU Na2, LIU Wei2*, WANG Ke-qing2, LI Chen-yuan1, CHEN Kun-long1, LI Yan-xiang1*. Research on Quantitative Model of Corrosion Products of Iron Artefacts Based on Raman Spectroscopic Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2166-2173. |
[3] |
CHU Zhi-hong1, 2, ZHANG Yi-zhu2, QU Qiu-hong3, ZHAO Jin-wu1, 2, HE Ming-xia1, 2*. Terahertz Spectral Imaging With High Spatial Resolution and High
Visibility[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(02): 356-362. |
[4] |
SHENG Qiang1, 2, ZHENG Jian-ming1*, LIU Jiang-shan2, SHI Wei-chao1, LI Hai-tao2. Advances and Prospects in Inner Surface Defect Detection Based on Cite Space[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(01): 9-15. |
[5] |
ZHAO Guo-qiang1, QIU Meng-lin1*, ZHANG Jin-fu1, WANG Ting-shun1, WANG Guang-fu1, 2*. Peak Splitting Method of Ion-Beam-Induced-Luminescence Spectrum Based on Voigt Function Fitting[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3512-3518. |
[6] |
GAO Shi-jiao1, GUAN Hai-ou1*, MA Xiao-dan1, WANG Yan-hong2. Soybean Canopy Extraction Method Based on Multispectral Image Processing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(11): 3568-3574. |
[7] |
WANG Xiao-bin1, 2, 3, ZHANG Xi1, GUAN Chen-zhi1, HONG Hua-xiu1, HUANG Shuang-gen2*, ZHAO Chun-jiang3. Quantitative Detection of Ascorbic Acid Additive in Flour Based on Raman Imaging Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(12): 3765-3770. |
[8] |
ZHANG Tie-zhu1, 2, ZHANG Yu-xuan2, 3, LIU Sai-yu2, 4, LI Hang-ren2, XU Wen-ce1, 2, ZHANG Jin-shan1*, OUYANG Shun-li2*, WU Nan-nan4. The Occurrence and Distribution of REE Minerals in Fluorite-Type Ores in Bayan Obo:Constraints From Raman Mapping[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(12): 3776-3781. |
[9] |
MA Xiao-dan1*, LIU Meng1, GUAN Hai-ou1, WEN Feng-rui1, LIU Gang2. Recognition Method for Crop Canopies Based on Thermal Infrared Image Processing Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(01): 216-222. |
[10] |
YAN Fan1, ZHU Qi-bing1*, HUANG Min1, LIU Cai-zheng1, LEI Ze-min2, ZHANG Heng2, ZHANG Li-wen2,LI Min2. Quantitative Analysis Method for Mixture With Known Components Based on Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(11): 3599-3605. |
[11] |
FAN Xian-guang1, 2, LIU Long1, ZHI Yu-liang1, KANG Zhe-ming1, XIA Hong1, ZHANG Jia-jie1, WANG Xin1, 2*. Fast Reconstruction for Multi-Channel Raman Imaging Based on and Sample Optimization and PCA[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(08): 2495-2499. |
[12] |
LI Zhen-bo1, 2, 3, NIU Bing-shan1, PENG Fang1, LI Guang-yao1. Estimation Method of Fry Body Length Based on Visible Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(04): 1243-1250. |
[13] |
FAN Xian-guang1, 2, 3, WU Teng-da1, ZHI Yu-liang1, WANG Xin1, 2, 3*. Denoising Method for Raman Imaging Data Based on Singular Value Decomposition and Median Absolute Deviation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(02): 436-440. |
[14] |
XI Yang, LI Yue-e*. A Novel Interpolation Method for Raman Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(02): 410-414. |
[15] |
SHENG Zhen-fei1, ZHANG Chun-guang1*, QIU Ze-long1, WANG Hao1, 2*, ZHANG Xiao-fa1, HUANG Xi1, TAN Zhi-wei1, QIU Wei-jie1, WANG Peng-chong1, 2*, LIU Wen-yao3, DUAN Mao-qiang1, 4, HUANG Xiao-li1, 5, HUANG Zu-fang1, LIU Yi-ping1, XING Yu-wei1, LIN Bin-bin1. Spectroscopic Imaging of Cutaneous Squamous Cell Carcinoma Based on Acousto-Optic Filtering[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(01): 34-40. |
|
|
|
|