低成本便携式多光谱成像系统的研发及优化
Development and optimization of a low-cost and portable multispectral imaging system
- 2021年26卷第8期 页码:1796-1808
纸质出版日期: 2021-08-16 ,
录用日期: 2021-05-28
DOI: 10.11834/jig.210189
移动端阅览
浏览全部资源
扫码关注微信
纸质出版日期: 2021-08-16 ,
录用日期: 2021-05-28
移动端阅览
朱豪男, 胡孟晗, 张健, 李庆利. 低成本便携式多光谱成像系统的研发及优化[J]. 中国图象图形学报, 2021,26(8):1796-1808.
Haonan Zhu, Menghan Hu, Jian Zhang, Qingli Li. Development and optimization of a low-cost and portable multispectral imaging system[J]. Journal of Image and Graphics, 2021,26(8):1796-1808.
目的
2
针对现有多光谱成像系统存在成本高、结构复杂、操作难度大和响应速度慢等问题。因此,本文提出了一种基于脉冲调制的低成本便携式多光谱成像系统,并采用客观图像质量评估(image quality assessment,IQA)的方法对其系统参数进行优化。
方法
2
该系统主要由光源模块、控制模块、图像采集模块和图像分析模块4部分组成。光源模块采用9个波长的LED (light emitting diode)阵列,其中心波长为365 nm、390 nm、460 nm、515 nm、585 nm、620 nm、650 nm、730 nm和840 nm;控制模块主要包括LED驱动电路和USB (universal serial bus)电源,可以通过发送一定时间间隔的脉冲波来分时点亮LED,并通过一定阻抗匹配使LED发光强度达到最大值;图像采集模块主要使用去除红外截止滤波片的高清红外工业相机,该相机的最佳光谱感应范围包含所选的9个LED灯珠的中心波长;图像分析模块主要执行客观图像质量评估算法。系统执行时,STC89C51单片机发射周期为
T
的脉冲波来驱动9种不同波长的LED分时点亮。然后,计算机平台调用高清红外相机模组,以相匹配的间隔捕获多光谱图像。在系统拍摄参数优化实验中,本文采用模糊度和清晰度评价指标对所获得的多光谱图像从相机拍摄时间间隔、相机拍摄距离和光照强度3个角度进行质量评估,进而获得较优的系统成像参数。
结果
2
通过改变系统拍摄参数,对3个场景下的不同拍摄条件所获取的多光谱图像质量进行评估,结果显示:对于本文所搭建的多光谱成像系统,相机拍摄时间间隔与LED灯珠频闪周期同步,拍摄距离为25 mm,光照强度为45 Lux下成像质量相对较好。
结论
2
本文设计并搭建的基于脉冲调制的低成本便携式多光谱成像系统成本低、操作难度小、结构简单、成像质量较好、成像速度较快,可以满足多光谱成像系统大规模推广使用的要求。此外,本文的系统设计方法、设计思路和实验方案等可以为后续研究提供借鉴。
Objective
2
Hyperspectral imaging systems are widely used in various fields owing to their image-spectral characteristic and unique "spectral fingerprint" information. Multispectral imaging systems are generally less costly and more suitable for the large-scale applications compared with hyperspectral imaging systems. Nonetheless
the existing multispectral imaging systems suffer from certain problems
such as high cost
complex structure
difficult operation
and slow response time. Accordingly
a low-cost portable multispectral imaging system based on pulse modulation is proposed in this study
and its imaging parameters are optimized using the objective image quality assessment methods.
Method
2
This system strives for a high degree of integration in a hardware design. The light source and control central processing unit(CPU) are integrated on a small printed circuit board(PCB). The 18 light emitting diode(LED) pairs of nine different wavelengths are integrated on a circular PCB board to form a circle by using a disc design. The light source can be converged
and the brightness can be improved to a certain extent. The proposed multispectral imaging system is mainly composed of a light source
a control
an image acquisition section
and an image analysis part. The light source part mainly includes nine LED arrays with the center wavelengths of 365 nm
390 nm
460 nm
515 nm
585 nm
620 nm
650 nm
730 nm
and 840 nm. The control part mainly includes the self-designed LED driver circuit and universal serial bus(USB) power supply
which can light up LED arrays by sending the pulse waves at certain time intervals in time and allows the LED arrays to reach the maximum luminous intensity through the certain impedance matching. The image acquisition part primarily consists of a high-definition infrared industrial camera without the near infrared(IR) cut-off filter
which has an optimal spectral sensing range encompassing the central wavelengths of the selected nine LED arrays. The computer is used to call OpenCV through the Python language to control the camera to take images at a certain frequency. The image analysis part mainly performs the objective image quality assessment algorithms. When the system is executed
the STC89C51 microcontroller emits a pulse wave with a period of
T
(
T
is adjustable) to drive nine different wavelengths of LED arrays to light up in time. Subsequently
the computer platform calls the camera modules to capture multispectral images at matching intervals. In the system optimization experiments
we use the sharpness and the blur metrics to objectively evaluate the quality of the obtained multispectral images from three perspectives of camera shooting interval
imaging distance
and light intensity
thus obtaining better system imaging parameters.
Result
2
The quality of multispectral images acquired from various shooting parameters and shooting conditions under three different scenarios are evaluated. Results show that the image quality of the developed multispectral imaging system is relatively good under the camera shooting interval synchronized with the bead strobe cycle of the LED arrays. The imaging distance is 25 mm
and the light intensity is 45 Lux.
Conclusion
2
The developed multispectral imaging system based on pulse modulation is low-cost
less difficult to operate
has a simple structure
has better imaging quality
has faster imaging speed
and can meet the requirements of large-scale promotion of multispectral imaging systems for various application domains. In addition
the system design methods
design ideas
and experimental protocols covered in the current work may provide references for the subsequent studies.
脉冲调制多光谱成像图像质量评价实验设计优化嵌入式系统图像处理
pulse modulationmultispectral imagingimage quality assessmentexperimental design optimizationembedded systemsimage processing
Ahmed A S, Kim H J, Kim J, Hwang K S and Kim S. 2017. Enhancing the responsivity of uncooled infrared detectors using plasmonics for high-performance infrared spectroscopy. Sensors, 17(4): #908[DOI: 10.3390/s17040908]
Bayarri V, Castillo E, Ripoll S, and Sebastián M A. 2021. Improved application of hyperspectral analysis to rock art panels from el Castillo cave (Spain). Applied Science, 11(3): #1292[DOI: 10.3390/app11031292]
Bolton F J, Bernat A S, Bar-Am K, Levitz D and Jacques S. 2018. Portable, low-cost multispectral imaging system: design, development, validation, and utilization. Journal of Biomedical Optics, 23(12): #121612[DOI: 10.1117/1.JBO.23.12.121612]
Chubala C M, Ensor T M, Neath I and Surprenant A M. 2020. Dynamic visual noise does not affect memory for fonts: redefining the image definition hypothesis. Experimental Psychology, 67(3): 161-168[DOI: 10.1027/1618-3169/a000491]
Gu K, Zhai G T, Lin W S, Yang X K and Zhang W J. 2015. No-reference image sharpness assessment in autoregressive parameter space. IEEE Transactions on Image Processing, 24(10): 3218-3231[DOI: 10.1109/TIP.2015.2439035]
Hu M H, Dong Q L and Liu B L. 2016. Comparison of predicting blueberry firmness and elastic modulus with hyperspectral reflectance, transmittance and interactance imaging modes. Spectroscopy and Spectral Analysis, 36(11): 3651-3656
胡孟晗, 董庆利, 刘宝林. 2016. 基于高光谱反射、透射和交互作用成像模式的蓝莓硬度和弹性模量预测的比较. 光谱与光谱学分析, 36(11): 3651-3656 [DOI: 10.3964/j.issn.1000-0593(2016)11-3651-06]
Hu M H and Li Q L. 2019. An efficient model transfer approach to suppress biological variation in elastic modulus and firmness regression models using hyperspectral data. Infrared Physics&Technology, 99: 140-151[DOI: 10.1016/j.infrared.2019.04.003]
Hu M H, Zhai G T, Xie R, Min X K, Li Q L, Yang X K and Zhang W J. 2020. A wavelet-predominant algorithm can evaluate quality of THz security image and identify its usability. IEEE Transactions on Broadcasting, 66(1): 140-152[DOI: 10.1109/TBC.2019.2901388]
Hua X, Pan C, Shi Y, Liu J G and Hong H Y. 2020. Removing atmospheric turbulence effects via geometric distortion and blur representation. IEEE Transactions on Geoscience and Remote Sensing: #3043627[DOI: 10.1109/TGRS.2020.3043627]
Li H, Li G, Ye Y P and Lin L. 2021. A high-efficiency acquisition method of LED-multispectral images based on frequency-division modulation and RGB camera. Optics Communications, 480: #126492[DOI: 10.1016/j.optcom.2020.126492]
Liu C, Tao R, Li W, Zhang M M, Sun W W and Du Q. 2021. Joint classification of hyperspectral and multispectral images for mapping coastal wetlands. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 982-996[DOI: 10.1109/JSTARS.2020.3040305]
Liu L X, Li M Z, Zhao Z G and Qu J L. 2018. Recent advances of hyperspectral imaging application in biomedicine. Chinese Journal of Lasers, 45(2): 214-223
刘立新, 李梦珠, 赵志刚, 屈军乐. 2018. 高光谱成像技术在生物医学中的应用进展. 中国激光, 45(2): 214-223 [DOI: 10.3788/CJL201845.0207017]
Narvekar N D and Karam L J. 2011. A no-reference image blur metric based on the cumulative probability of blur detection (CPBD). IEEE Transactions on Image Processing, 20(9): 2678-2683[DOI: 10.1109/TIP.2011.2131660]
Oszust M, Piórkowski A and Obuchowicz R. 2020. No-reference image quality assessment of magnetic resonance images with high-boost filtering and local features. Magnetic Resonance in Medicine, 84(3): 1648-1660[DOI: 10.1002/mrm.28201]
Rong N C and Huang M Z. 2020. Age estimation of bloodstains based on visible-near infrared multi-spectrum combined ensembling model. Spectroscopy and Spectral Analysis, 40(1): 168-173
戎念慈, 黄梅珍. 2020. 可见-近红外多光谱和多种算法模型融合的血迹年龄预测. 光谱学与光谱分析, 40(1): 168-173 [DOI: 10.3964/j.issn.1000-0593(2020)01-0168-06]
Vu C T, Phan T D and Chandler D M. 2012. S3: a spectral and spatial measure of local perceived sharpness in natural images. IEEE Transactions on Image Processing, 21(3): 934-945[DOI: 10.1109/TIP.2011.2169974]
Wang R, Nie F P, Wang Z, He F and Li X L. 2020. Multiple features and isolation forest-based fast anomaly detector for hyperspectral imagery. IEEE Transactions on Geoscience and Remote Sensing, 58(9): 6664-6676[DOI: 10.1109/TGRS.2020.2978491]
Zhai C J and Zhou G X. 2020. Acquisition of multi-spectrum fingerprint image with a smartphone[J/OL]. Laser Technology. [2021-03-02]
翟春婕, 周桂雪. 2020. 基于智能手机的多光谱指纹图像采集研究[J/OL]. 激光技术. [2021-03-02].https://kns.cnki.net/KCMS/detail/detail/51.1125.TN.20201209.1327.002.htmlhttps://kns.cnki.net/KCMS/detail/detail/51.1125.TN.20201209.1327.002.html
Zhai G T and Min X K. 2020. Perceptual image quality assessment: a survey. Science China Information Sciences, 63(11): #211301[DOI: 10.1007/s11432-019-2757-1]
Zhang B H, Liu L S, Gu B X, Zhou J, Huang J C and Tian G Z. 2018. From hyperspectral imaging to multispectral imaging: portability and stability of HIS-MIS algorithms for common defect detection. Postharvest Biology and Technology, 137: 95-105[DOI: 10.1016/j.postharvbio.2017.11.004]
Zhang Q, Chen W N and Hao H G. 2020. A review of research on hyperspectral imaging technology in document inspection applications. Applied Chemical Industry, 49(1): 165-170
张倩, 陈维娜, 郝红光. 2020. 高光谱成像技术在文件检验应用的研究综述. 应用化工, 49(1): 165-170 [DOI: 10.3969/j.issn.1671-3206.2020.01.037]
相关作者
相关机构