Balkan Journal of Electrical and Computer Engineering 2147-284X 2147-284X MUSA YILMAZ 10.17694/bajece.802855 Computer Software Software Testing, Verification and Validation Bilgisayar Yazılımı Yazılım Testi, Doğrulama ve Validasyon A Image Enhancement Method For Night-Way Images https://orcid.org/0000-0003-0673-469X Turan Bülent Gaziosmanpaşa Üniversitesi 01 30 2021 9 1 8 16 09 30 2020 12 24 2020 Copyright © 2013, Balkan Journal of Electrical and Computer Engineering 2013 Balkan Journal of Electrical and Computer Engineering

Image processing has a wide range of applications especially in our daily lives. Image processing is not common in sensitive industrial applications. Because of these applications, very high percentage of success is requested. Also these applications work in real-time. However, it can be widely used in many daily routines (driving, entrance to the workplace/ exit, control of multimedia devices, security applications, identification applications, etc.). Especially Advanced Driver Assistance Systems (ADAS) is a popular working area for image processing. Strip tracking systems, pedestrian detection systems, reading of traffic signs and signals are based on image processing. In this study, a new method has been developed to increase the visibility levels of road images at night driving. In these images, the brightness level is low because of insufficient of light sources (headlights and road lighting) which are often used to increase the driver's view. On the other hand, adversely affects the view of driver which the headlight of coming vehicles from opposite directions, poorly structured road lighting and etc. Especially the vehicle headlights coming from the opposite direction take the eye of the drivers and cause the level of view to decrease.Intense dark areas and light sources are in the image together. By so, special to these images requires the use of an adaptive improvement method. This is because, when classical image enhancement methods are used, the visibility levels of the dark areas are increased, and the shining regions are more likely to shine and the visibility level decreases in these regions.The developed method aims at enhancement these images that drivers be exposed to. For this purpose, the light sources in the image and the magnitudes of these light sources, the distance of the pixels to be calculated from the light sources, the value of the pixel itself and the neighboring pixels are used as separate parameters. Images are enhancement with the equations developed using these parameters. When the output images obtained with the use of the developed equations and the obtained Structural Similarity İndex Maps (SSIM) are examined, it is seen that the developed method gives good results.

 ADAS early warning image enhancement night road images pedestrian detection K. W. Gish, M. Shoulson, & M. Perel, 2002. “Driver behavior and performance using an infrared night vision enhancement system” Presented at the 80th Annual Meeting of the Transportation Research Board, Washington, D.C. F. Xu, X. Liu, and K. Fujimura, (2005) "Pedestrian Detection and Tracking with Night Vision" IEEE Trans. Intelligent Transportation Systems, vol. 6, no. 1, pp. 63-71, Mar. 2005. https://doi.org/10.1109/TITS.2004.838222 O. Tsimhoni, J. Bärgman and M.J. Flannagan (2007) “Pedestrian Detection with near and far Infrared Night Vision Enhancement”, LEUKOS, 4:2, 113-128 D. Olmeda, C. Premebida, U. Nunes, J.M. Armingol, A. de la Escalera, (2013) “Pedestrian detection in far infrared images”, Integr. Comput. Aided Eng. 2013, 20, 347–360. https://doi.org/10.3233/ICA-130441 A. González, Z. Fang, Y. Socarras, et al. (2016) ”Pedestrian detection at Day/Night time with visible and FIR cameras”, a comparison 820 Sensors, 16 (6) (2016) :1-820:11. https://doi.org/doi:10.3390/s16060820 G. Wang, Q. Liu, Q. Wu, (2016) "Far-infrared pedestrian detection for advanced driver assistance systems using scene context", Optical Engineering 55(4), 043105 (21 April 2016). https://doi.org/10.1117/1.OE.55.4.043105 K. Bengler, K. Dietmayer, B. Faerber, et al. (2014) “Three decades of driver assistance systems: review and future perspectives, IEEE Intell. Transp. Syst. Mag., 2014, 6, (4), pp. 6–22 https://doi.org/10.1109/MITS.2014.2336271 S. Mahlke, D. Rösler, K. Seifert, J.F. Krems, M. Thüring (2007) “Evaluation of six night vision enhancement systems: qualitative and quantitative support for intelligent image processing”, Human Factors 49 (3), 518–531. https://doi.org/10.1518/001872007X200148 V. Asari, A. Livingston, M. Zhang, H. Ngo and L. Tao, (2005)"A Multi-sensor Image Fusion and Enhancement System for Assisting Drivers in Poor Lighting Conditions," 34th Applied Imagery and Pattern Recognition Workshop (AIPR'05)(AIPR), Washington, DC, 2005, pp. 106-113. https://doi.org/10.1109/AIPR.2005.9 H.A. Burley, R. J. Sweet, (1991) “Night vision system with color video camera”, US5001558A * General Motors Corporation. US Patent 5,001,558 Robert Tamburo, Eriko Nurvitadhi, Abhishek Chugh, Mei Chen, Anthony Rowe, Takeo Kanade, Srinivasa G. Narasimhan, “Programmable Automotive Headlights” Computer Vision – ECCV 2014. ECCV 2014. Lecture Notes in Computer Science, vol 8692. pp 750-765 Springer, Cham A. Borkar, M. Hayes, M. T. Smith, and S. Pankanti, (2009) “A layered approach to robust lane detection at night,”inProc.IEEEWorkshopComput.Intell. Vehicles Vehicular Syst., Apr. 2009, pp. 51–57. https://doi.org/10.1109/CIVVS.2009.4938723 Pomerleau D (1997) “Visibility estimation from a moving vehicle using the RALPH vision system”, In: Proceedings of the IEEE Conference on Intelligent Transportation Systems, Boston, Mass., November 1997, p403 https://doi.org/10.1109/ITSC.1997.660594 PELI, E. 1990. “Contrast in complex images” J. Opt. Soc. Am. A 7, 10 (October), 2032–2040. https://doi.org/10.1364/JOSAA.7.002032 S. M. Pizer, E. P. Amburn, J. D. Austin, R. Cromartie, A. Geselowitz, T. Greer, B. H. Romeny, J. B. Zimmerman, K. Zuiderveld, "Adaptive histogram equalization and its variations", Comp. Vis. Graph. Image Process., vol. 39, no. 3, pp. 355-368, 1987. https://doi.org/10.1016/S0734-189X(87)80186-X T. Kim, J. Paik, "Adaptive contrast enhancement using gain-controllable clipped histogram equalization", IEEE Trans. on Consumer Electronics, vol. 54, no. 4, pp. 1803-1810, November 2008. https://doi.org/10.1109/TCE.2008.4711238 Liyun Zhuang, Yepeng Guan, 2018, “Adaptive Image Enhancement Using Entropy-Based Subhistogram Equalization” Computational Intelligence and Neuroscience, Volume 2018, Article ID 3837275, 13 pages, https://doi.org/10.1155/2018/3837275 N. Hautière, J.-P. Tarel, D. Aubert, E. Dumont, "Blind contrast enhancement assessment by gradient ratioing at visible edgese", Image Analysis & Stereology Journal, vol. 27, no. 2, pp. 87-95, june 2008. https://doi.org/10.5566/ias.v27.p87-95 Tarel, J.P., Hautière, N., Caraffa, L., et al.: ‘Vision enhancement in homogeneous and heterogeneous fog’, IEEE Intell. Transp. Syst. Mag., 2012, 4, (2), pp. 6–20, https://doi.org/10.1109/MITS.2012.2189969 X. B. Jin, J. Bao, and J. J. Du, “Image Enhancement Based on Selective - Retinex Fusion Algorithm” Journal of Software, vol. 7, no. 6, pp. 1187–1194, June 2012 https://pdfs.semanticscholar.org/2293/fd6124403f44e59134755064c6118989f180.pdf Z. Shi, M. M. Zhu, B. Guo, M. Zhao, C. Zhang, "Nighttime low illumination image enhancement with single image using bright/dark channel prior", EURASIP Journal on Image and Video Processing, vol. 2018, pp. 13, February 2018. https://doi.org/10.1186/s13640-018-0251-4 Ji Wei, Qian Zhijie, Xu Bo and Zhao Dean, (2018) “A Nighttime İmage Enhancement Method Based On Retinex And Guided Filter For Object Recognition Of Apple Harvesting Robot” International Journal of Advanced Robotic Systems, January-February 2018: 1–12, https://doi.org/10.1177/1729881417753871 R. Nivedha, W. Newton David Raj M.Tech., (2016) “Hardware Implementation Of Combining Image Enhancement And Roı Extraction For Night Time Images” Int. J. Advanced Networking and Applications Volume No: 8, Issue No: 4(Jan-Feb 2017), Special Issue-NCBSI-2016 https://www.ijana.in/specialissue.php#one Hulin Kuang, Xianshi Zhang, Yong-Jie Li, Leanne Lai Hang Chan, Hong Yan, (2017) “Nighttime Vehicle Detection Based on Bio-Inspired Image Enhancement and Weighted Score-Level Feature Fusion” IEEE Transactions on Intelligent Transportation Systems archive , Volume 18 Issue 4, April 2017 Pages 927-936, https://doi.org/10.1109/TITS.2016.2598192 Allen M. Waxman, Eugene D. Savoye, David A. Fay, Mario Aguilar, Alan N. Gove, James E. Carrick, Joseph P. Racamato, "Electronic imaging aids for night driving: low-light CCD, uncooled thermal IR, and color-fused visible/LWIR", Proc. SPIE 2902, Transportation Sensors and Controls: Collision Avoidance, Traffic Management, and ITS, (17 February 1997); https://doi.org/10.1117/12.267163 P. Didyk, R. Mantiuk, M. Hein and H.P. Seidel, (2008) “Enhancement Of Bright Video Features For Hdr Displays” Computer Graphics Forum, Volume27, Issue4 June 2008 Pages 1265-1274, https://doi.org/10.1111/j.1467-8659.2008.01265.x Gang Cao, Lihui Huang, Huawei Tian, Xianglin Huang, Yongbin Wang, Ruicong Zhi, (2017) “Contrast Enhancement of Brightness-Distorted Images by Improved Adaptive Gamma Correction” Computers & Electrical Engineering, Volume 66, February 2018, Pages 569-582, https://doi.org/10.1016/j.compeleceng.2017.09.012 MinjieWan, Guohua Gu, Weixian Qian, Kan Ren, Qian Chen, Xavier Maldague, (2018) “Infrared Image Enhancement Using Adaptive Histogram Partition and Brightness Correction” Remote Sens. 2018, 10(5), 682; https://doi.org/10.3390/rs10050682 Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, and Eero P. Simoncelli, (2004) “Image Quality Assessment: From Error Visibility to Structural Similarity “IEEE Transactıons On Image Processıng, Vol. 13, No. 4, pp. 600-612, April, 2004. https://doi.org/10.1109/TIP.2003.819861 Jing Rui Tang, Nor Ashidi Mat Isa, (2014) “Adaptive Image Enhancement based on Bi-Histogram Equalization with a clipping limit” Computers and Electrical Engineering 40 (2014) 86-103. https://doi.org/10.1016/j.compeleceng.2014.05.017 TTY Motorlu Araçlar 2, https://vimeo.com/96782778. Last access date: 18.02.2019 HD YOL KAMERASI GECE PERFORMANSI (şehir içi), https://www.youtube.com/watch?v=Icbl5wQDOFo. Last access date: 18.02.2019 ARAÇ KAMERASI Full HD 1080P ARAÇ iÇi KAMERA GECE KAYIT VİDEOSU, https://www.youtube.com/watch?v=lRV4JQQ7wwI. Last access date: 18.02.2019 Late Night Mountain Road Drive, https://www.youtube.com/watch?v=P49yLhhr0O0. Last access date: 18.02.2019 Rabbit runs in front of car, https://www.youtube.com/watch?v=O1kMF6BCG2I. Last access date: 18.02.2019 Riding towards Shimla ?? BE CAREFUL !! FOX spotted on highway, https://www.youtube.com/watch?v=teamtsm88cI. Last access date: 18.02.2019