Analysis and restoration research of fog polarization imaging

WANG Jiejun; YANG Jie; ZHANG Wentao; WANG Xinqiang; YE Song

doi:10.7510/jgjs.issn.1001-3806.2016.04.014

LASER TECHNOLOGY > 2016 > 40(4): 521-525. > DOI: 10.7510/jgjs.issn.1001-3806.2016.04.014

WANG Jiejun, YANG Jie, ZHANG Wentao, WANG Xinqiang, YE Song. Analysis and restoration research of fog polarization imaging[J]. LASER TECHNOLOGY, 2016, 40(4): 521-525. DOI: 10.7510/jgjs.issn.1001-3806.2016.04.014

Citation:

PDF (9352 KB)

Analysis and restoration research of fog polarization imaging

WANG Jiejun^1,2,3,
YANG Jie¹,
ZHANG Wentao^1,2,3,
WANG Xinqiang^1,2,3,
YE Song^1,2,3

1.
School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China;
2.
Guangxi Colleges and Universities Key Laboratory of Optoelectronic Information Processing, Guilin University of Electronic Technology, Guilin 541004, China;
3.
Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of ElectronicTechnology, Guilin 541004, China

More Information

Received Date: April 29, 2015
Revised Date: June 07, 2015
Published Date: July 24, 2016

Graphical Abstract

Abstract

Abstract

To solve the quality degradation problem of fog polarization imaging, an improved defogging method was proposed based on physical model of atmospheric scattering and dark passage principle of polarization images. Firstly, based on atmospheric scattering model, fog polarization imaging mechanism was analyzed and effect of atmospheric polarization on defogging was explained. Secondly, based on edge detection operator and closing operation, sky region of fog polarization image was obtained, and light intensity of infinity atmospheric and degree of polarization of atmospheric were estimated. At last, to solve the existing factors in the image such as noise interference, radiation intensity information of the degraded image was restored by modifying the degree of polarization and light intensity distribution of atmospheric. After theoretical analysis and experimental verification, good results of foggy image restoration were achieved. The results show that the algorithm can accurately obtain the sky region and improve the contrast and sharpness of the image, and improve the degradation of the image. Therefore, the algorithm can effectively inhibit the degradation of the image caused by fog, and improved target detection and identification capability of remote sensing.
- scattering,
- polarization,
- filter,
- image restoration

FullText(HTML)

References (15)

References

[1]	TREIBITZ T, SCHECHNER Y Y. Recovery limits in pointwise degradation[C]//Computational Photography. Washington DC, USA:IEEE Computer Society, 2009:1-8.
[2]	FATTAL R. Single image dehazing[J]. ACM Transaction on Graphics, 2008, 27(3):72-80.
[3]	TAN R T. Visibility in bad weather from a single image[C]//Computer Vision and Pattern Recognition. Washington DC, USA:IEEE Computer Society, 2008:1-7.
[4]	KOPF J, NEUBERT B, CHEN B, et al. Deep photo:Model-based photograph enhancement and viewing[J]. ACM Transactions on Graphics, 2008, 27(5):1-10.
[5]	TAN K, OAKLEY J. Physics-based approach to color image enhancement in poor visibility conditions[J]. Journal of the Optical Society of America, 2001,A18(10):2460-2467.
[6]	HE K M, SUN J, TANG X O. Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(12):2341-2353.
[7]	ENESI I, MIHO R. A fast algorithm for contrast restoration of weather degraded images[C]//Complex, Intelligent and Software Intensive Systems (CISIS). Washington DC, USA:IEEE Computer Society, 2012:636-641.
[8]	NAMER E, SHWARTZ S, SCHECHNER Y Y. Skyless polarimetric calibration and visibility enhancement[J]. Optics Express, 2009, 17(2):472-493.
[9]	SCHECHNER Y Y, NARASIMHAN S G, NAYAR S K. Polarization-based vision through haze[J]. Appled Optics, 2003, 42(3):511-525.
[10]	KAFTORY R, SCHECHNER Y Y, ZEEVI Y Y. Variational distance-dependent image restoration[C]//Computer Vision and Pa-ttern Recognition. Washington DC, USA:IEEE Computer Society, 2007:1-8.
[11]	SCHECHNER Y Y, AVERBUCH Y. Regularized image recovery in scattering media[J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, 29(9):1655-1660.
[12]	ZHOU P Ch, XUE M G, ZHANG H K, et al. Automatic image dehaze using polarization filtering[J]. Journal of Image and Graphics, 2011, 16(7):1178-1183(in Chinese).
[13]	XIA H L, LI G, ZHANG R B, et al. Image defogging algorithm based on polarisation characteristics[J]. Computer Applications and Software, 2014, 31(10):224-226(in Chinese).
[14]	TREIBITZ T, SCHECHNER Y Y. Polarization:beneficial for visibility enhancement[C]//Computer Vision and Pattern Recognition. Washington DC, USA:IEEE Computer Society, 2009:525-532.
[15]	LIANG T Q, ZHAO Q, SUN X B, et al. Research on image restoration by polarized remote sensing through haze[J]. Geomatics and Information Science of Wuhan University, 2014, 39(2):244-247(in Chinese).

Cited By

Get Citation

PDF

XML

Article views (4) PDF downloads (5)

Turn off MathJax

Article Contents

Abstract

References

Analysis and restoration research of fog polarization imaging

Abstract

References

Catalog

Links：

Analysis and restoration research of fog polarization imaging

Abstract

References

Catalog

Links：

Export File

Citation

Format

Content