Reflection separation technology based on polarization characteristics

doi:10.23919/JSEE.2022.000101

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (5): 1032-1042.doi: 10.23919/JSEE.2022.000101

• ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

Reflection separation technology based on polarization characteristics

Yan ZHANG, Jinghua ZHANG*(), Zhiguang SHI(), Yu ZHANG(), Feng LING

¹ National Key Laboratory of Science and Technology on Automatic Target Recognition, College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China

Received:2021-07-26 Online:2022-10-27 Published:2022-10-27
Contact: Jinghua ZHANG E-mail:965477460@qq.com;szgstone75@sina.com;zhangyu17d@nudt.edu.cn
About author:|ZHANG Yan was born in 1975. She received her B.E., M.E., and Ph.D. degrees in information and communication engineering from National University of Defense Technology, Changsha, in 1997, 2001, and 2008, respectively, where she is currently a professor with the National Key Laboratory of Science and Technology on Automatic Torget Recognition. Her research interests include infrared image processing, infrared polarization imaging, automatic target recognition, and target tracking. E-mail: atrthreefire@sina.com||ZHANG Jinghua was born in 1994. He received his M.S. degree in information and communication engineering from National University of Defense Technology, in 2018. He is a Ph.D student in the National Key Laboratory of Science and Technology on Automatic Torget Recognition. His research interests include image processing and automatic target recognition. E-mail: 965477460@qq.com||SHI Zhiguang was born in 1975. He received his M.S. and Ph.D. degrees in information and communication engineeing from National University of Defense Technology, China, in 2002 and 2007, respectively. He is currently an associate research fellow. His research interests are ladar image processing and automatic target recognition. E-mail: szgstone75@sina.com||ZHANG Yu was born in 1995. He received his M.S. degree in information and communication engineering from National University of Defense Technology, in 2019. He is a Ph.D student in the National Key Laboratory of Science and Technology on Automatic Torget Recognition. His research interests are image processing and automatic target recognition. E-mail: zhangyu17d@nudt.edu.cn||LING Feng was born in 1996. He received his B.S. degree in electronic information engineering from Jilin University, China, in 2019. He is a M.S. student in the National Key Laboratory of Science and Technology on Automatic Torget Recognition. His research interests include image processing and automatic target recognition. E-mail: 1362904633@qq.com
Supported by:
This work was supported by the National Natural Science Foundation of China (62075239; 61302145)

Abstract

Abstract:

Specific to the reflected light problem on the surface of transparent body, the polarization characteristics of the reflection region are analyzed, and a polarization characterization model combining the reflection and transmission effects is established. On the basis of the polarization characteristic analysis, the minimum value of normalized cross-correlation (NCC) coefficient between transmission and reflection images is solved through the gradient descent method, and their polarization degrees under the minimum correlation are acquired. According to the distribution relations of the transmitted and reflected lights in perpendicular and parallel directions, reflection separation is realized via the polarized orthogonality difference algorithm based on the degree of reflection polarization and the degree of transmission polarization.

Key words: reflection separation, transparent object, correlation, polarization characteristics

Yan ZHANG, Jinghua ZHANG, Zhiguang SHI, Yu ZHANG, Feng LING. Reflection separation technology based on polarization characteristics[J]. Journal of Systems Engineering and Electronics, 2022, 33(5): 1032-1042.

Figures/Tables 7

Fig 1

Fig 2

Fig 3

Fig 4

Fig 5

Fig 6

Table 1

References 30

1	LYU Y W, CUI Z P, LI S, et al Reflection separation using a pair of unpolarized and polarized images. Proc. of the 33rd Conference on Neural Information Processing Systems, 2019, 14492- 14502.
2	LI C, YANG Y X, HE K, et al Single image reflection removal through cascaded refinement. Proc. of the Conference on Computer Vision and Pattern Recognition, 2020, 3562- 3571.
3	WAN R J, SHI B X, LI H L, et al Reflection scene separation from a single image. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2020, 2395- 2403.
4	WEN Q, TAN Y J, QIN J, et al Single image reflection removal beyond linearity. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, 2395- 2403.
5	LEI C Y, HUANG X H, ZHANG M D, et al Polarized reflection removal with perfect alignment in the wild. Proc. of the Conference on Computer Vision and Pattern Recognition, 2020, 1747- 1755.
6	WEN S J, ZHENG Y Q, LU F Polarization guided specular reflection separation. IEEE Trans. on Image Processing, 2021, 30, 7280- 7291. doi: 10.1109/TIP.2021.3104188.Epub2021Aug20
7	ZHAO F, DONG Y, ZHANG J L Polarization visualization for low-irradiance regions by perceptually uniform color space. Defence Technology, 2021, 17 (2): 505- 511.
8	CHEN W, QIAO Y L, SUN X B, et al Method for water surface sun glint suppression based on polarized radiation image fusion. Acta Optica Sinica, 2019, 39 (5): 529001. doi: 10.3788/AOS201939.0529001
9	SANCHEZ-HERNANDEZ H H, PEREZ-ABARCA J M, CRUZ-FELIX A S, et al Study of the polarization mode by reflection under the excitation of the superficial polariton plasmon on the prism structure. Optics Communications, 2021, 478, 126403. doi: 10.1016/j.optcom.2020.126403
10	LI Y, BROWN M S. Single image layer separation using relative smoothness. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2014: 2752−2759.
11	OHNISHI N, KUMAKI K, YAMAMURA T, et al Separating real and virtual objects from their overlapping images. Proc. of the European Conference on Computer Vision, 1996, 636- 646.
12	TAN Z Y, ZHAO B L, XU X B, et al Object segmentation based on refractive index estimated by polarization of specular reflection. Optik-International Journal for Light and Electron Optics, 2019, 163918.
13	ZHANG C, WU X, XIE J Infrared polarization characteristics on sea surface based on bidirectional reflection distribution function. Optics and Precision Engineering, 2020, 28 (6): 1303- 1313.
14	CONG P H , ROBLES-KELLY A , HANCOCK Shape and refractive index recovery from single-view polarisation images. Proc. of the IEEE 23rd Conference on Computer Vision and Pattern Recognition, 2010, 1229- 1236.
15	PING X X, LIU Y, DONG X M, et al 3D reconstruction of textureless and high-reflective target by polarization and binocular stereo vision. Journal of Infrared and Millimeter Waves, 2017, 36 (4): 432- 438.
16	ZHANG X, NG R, CHEN Q F Single image reflection separation with perceptual losses. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, 4786- 4794.
17	MOREL O, MERIAUDEAU F, STOLZ C, et al Polarization imaging applied to 3D reconstruction of specular metallic surfaces. Proc. of the SPIE, 2005, 5679, 178- 186. doi: 10.1117/12.586815
18	KRISHNAN D, SHIH Y C, DURAND F, et al Reflection removal using ghosting cues. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, 3193- 3201.
19	WOLFF L B, BOULT T E Constraining object features using a polarization reflectance model. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1991, 13 (7): 635- 657. doi: 10.1109/34.85655
20	WOLFF L B Polarization-based material classification from specular reflection. IEEE Trans. on Pattern Analysis and Machine Intelligence, 1990, 12 (11): 1059- 1071.
21	WOLFF L B Using polarization to separate reflection components. Proc. of the IEEE International Conference on Computer Vision, 1989, 363- 369.
22	SCHECHNER Y Y, SHAMIR J, KIRYATI N Polarization and statistical analysis of scenes containing a semireflector. Journal of the Optical Society of America A, 2000, 17 (2): 276- 284. doi: 10.1364/JOSAA.17.000276
23	KONG N, TAI Y W, SHIN S Y High-quality reflection separation using polarized images. IEEE Trans. on Image Processing, 2011, 20 (12): 3393- 3405. doi: 10.1109/TIP.2011.2155080
24	FARID H, ADELSON E H Separating reflections and lighting using independent component analysis. IEEE Trans. on Computer Vision & Pattern Recognition, 1999, 1 (9): 1262.
25	CUI Z P, GU J W, SHI B X, et al Polarimetric multi-view stereo. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, 369- 378.
26	TERRIER P, DEVLAMINCK V, CHARBOIS J M Segmentation of rough surfaces using a polarization imaging system. Journal of the Optical Society of America. A, Optics Image Science & Vision, 2008, 25 (2): 423- 430.
27	ANDREW R, CHRIS P, GEORGE L Polarized emissivity and Kirchhoff’s law. Applied Optics, 1999, 38 (8): 1384- 1387.
28	ZHANG J H, ZHANG Y, SHI Z G Study and modeling of infrared polarization characteristics based on sea scene in long wave band. Journal of Infrared and Millimeter Waves, 2018, 37 (5): 586- 594.
29	ZHANG J H, ZHANG Y, SHI Z G Long-wave infrared polarization feature extraction and image fusion based on the orthogonality difference method. Journal of Electronic Imaging, 2018, 27 (2): 023021.
30	LI N, ZHAO Y Q, PAN Q, et al Removal of reflections in LWIR image with polarization characteristics. Optics Express, 2018, 26 (13): 16488. doi: 10.1364/OE.26.016488

Scene type	Evaluation index	Proposed algorithm	Literature [10]	Literature [11]	Literature [24]
Scene I	SSIM	0.8500	0.6338	0.7036	0.8262
	PSNR	25.6150	21.1347	21.6488	24.8754
	CORR	0.9228	0.6884	0.7422	0.8969
Scene II	SSIM	0.9230	0.7267	0.7345	0.9071
	PSNR	26.3443	19.5646	15.3712	23.0539
	CORR	0.9689	0.8175	0.7514	0.9629
Scene III	SSIM	0.9259	0.6879	0.8330	0.8744
	PSNR	29.9532	23.8244	23.6089	25.0559
	CORR	0.9568	0.7916	0.8255	0.8859
Scene IV	SSIM	0.9107	0.7163	0.8120	0.8713
	PSNR	28.4583	19.7837	20.0230	25.4024
	CORR	0.9815	0.8582	0.8941	0.9793

[1]	Lingchi GE, Min FANG, Haikun LI, Bo CHEN. Label correlation for partial label learning [J]. Journal of Systems Engineering and Electronics, 2022, 33(5): 1043-1051.
[2]	Yuhan LI, Wei QI, Zhenmiao DENG, Maozhong FU, Yunjian ZHANG. Monopulse instantaneous 3D imaging for wideband radar system [J]. Journal of Systems Engineering and Electronics, 2021, 32(1): 53-67.
[3]	Salem TITOUNI, Khaled ROUABAH, Salim ATIA, Mustapha FLISSI, Salaheddine MEZAACHE, Mohamed Salim BOUHLEL. Spectral transformation-based technique for reducing effect of limited pre-correlation bandwidth in the GNSS receiver filter in presence of noise and multipath [J]. Journal of Systems Engineering and Electronics, 2020, 31(2): 252-265.
[4]	Qian WANG, Feng SHANG, Liming DU, Wenjia ZHOU. Influence of B1 code correlation loop for vector tracking structures under complicated environment [J]. Journal of Systems Engineering and Electronics, 2019, 30(6): 1053-1063.
[5]	Yuanfa JI, Xiaoqian CHEN, Qiang FU, Xiyan SUN, Weimin ZHEN. Reconstruction of sub cross-correlation cancellation technique for unambiguous acquisition of BOC(kn, n) signals [J]. Journal of Systems Engineering and Electronics, 2019, 30(5): 852-860.
[6]	Wenjuan JIA, Juntao GAO, Peng ZHANG. Linear complexity and autocorrelation of a new class of binary generalized cyclotomic sequences of order two and length pqr [J]. Journal of Systems Engineering and Electronics, 2019, 30(4): 651-661.
[7]	Hongwei ZHAO, Zichun ZHANG, Xianzhi LUO, Qiuping WANG. Quality monitoring and biases estimation of BOC navigation signals [J]. Journal of Systems Engineering and Electronics, 2019, 30(3): 474-484.
[8]	Xu Wang, Quan Sun. Consistency check of degradation mechanism between natural storage and enhancement test for missile servo system [J]. Journal of Systems Engineering and Electronics, 2019, 30(2): 415-424.
[9]	Bo Wang, Xiaolong Liang, Liang Wei, and Pingni Liu. Aviation multi-station collaborative detecting based on time-frequency correlation of data-link [J]. Systems Engineering and Electronics, 2017, 28(5): 827-840.
[10]	Chengzhi Yang, Zhiwei Xiong, Yang Guo, and Bolin Zhang. LPI radar signal detection based on the combination of FFT and segmented autocorrelation plus PAHT [J]. Systems Engineering and Electronics, 2017, 28(5): 890-899.
[11]	Jujie Zhang, Min Fang, and Huimin Chai. Multi-label local discriminative embedding [J]. Systems Engineering and Electronics, 2017, 28(5): 1009-1018.
[12]	Xiaoyu Li, Jing Jin, Yi Shen, and Yipeng Liu. Noise level estimation method with application to EMD-based signal denoising [J]. Systems Engineering and Electronics, 2016, 27(4): 763-.
[13]	Qingxi Zeng, Linlin Tang, Pengna Zhang, and Ling Pei. Fast acquisition of L2C CL codes based on combination of hyper codes and averaging correlation [J]. Journal of Systems Engineering and Electronics, 2016, 27(2): 308-318.
[14]	Gongjian Zhou, Junhao Xie, Rongqing Xu, and Taifan Quan. Sequential nonlinear tracking filter without requirement of measurement decorrelation [J]. Systems Engineering and Electronics, 2015, 26(6): 1135-1141.
[15]	Shuxia Guo, Yafeng,Ruibing Liu, and Ying Gao. Multi-dimensional and complicated electromagnetic interference hardware-in-the-loop simulation method [J]. Systems Engineering and Electronics, 2015, 26(6): 1142-1148.

Reflection separation technology based on polarization characteristics

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

Share this article

Figures/Tables 7

References 30

Related Articles 15

Recommended Articles

Metrics

Comments