Enhancement of Images Taken in Fog Condition: A Review

• Autorzy: Das, Rajashree , Rajkonwar, Tridipjit , Bora, Dibya jyoti
• Konferencja: International Conference on Research in Management & Technovation (05-06.12.2020 ; Nagpur, Indie)
• Języki publikacji: EN

Abstrakty

EN

Images captured using camera systems in foggy weather conditions often suffer from poor visibility and can be seriously degraded due to atmospheric conditions, which creates a lot of impacts on the outdoor computer vision systems. To solve this problem, image enhancement is very important as this process is used for enhancing the quality of an image, and for this purpose numerous visibility enhancement techniques have been used and applied. In this paper, we have tried to describe how to enhance an image using different techniques and methods. For this, various techniques and methods have been studied for image enhancement used in different research and review papers. The main goal of this paper is to understanding and reviewing the techniques used for image enhancement.

Słowa kluczowe

PL

warunki atmosferyczne; wizja komputerowa; poprawa widoczności

EN

atmospheric conditions; computer vision; visibility enhancement

• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2020
• Tom: Vol. 24
• Strony: 5--9
• Opis fizyczny: Bibliogr. 12 poz., rys., tab.

Twórcy

autor

Das, Rajashree

• Department of Information Technology, School of Computing Science, Kaziranga University, Assam, India

autor

Rajkonwar, Tridipjit

• Department of Information Technology, School of Computing Science, Kaziranga University, Assam, India

autor

Bora, Dibya jyoti

• Department of Information Technology, School of Computing Science, Kaziranga University, Assam, India

Bibliografia

• 1. Ping-Juei Liu, Shi-Jinn Horng, Jzau-Sheng Lin, “Contrast in Haze Removal:Configurable Contrast enhancement Model Based on Dark Channel Prior,” IEEE Transactions on Image Processing, pp.2212-2227, 2018.
• 2. Zheqi Lin, “Dehazing for Image and Video Using Guided Filter,” Open Journal of Applied Sciences, pp.123-127,2012.
• 3. R.Ahila Priyadarshini, S.Aruna, “Visibility Enhancement Technique for Hazy Scenes,” 2018 4th International Conference on Electrical Energy Systems, 2018.
• 4. Mohammad Javad Abbaspour, Mehran Yazdi, Mohammadali Masnadi-shirazi, “ A new fast method for foggy image enhancement,” 2016 24th Iranian Conference on Electrical Engineering, pp.4-179,2016
• 5. Ashok Shrivastava, Sanjay Jain, “Single image dehazing based on one dimensional linear filtering and adoptive histogram equalization method,” 2016 international Conference on electrical Electronics, and Optimization Techniques, pp.2-235,2016.
• 6. S. S. Negi, Y. S Bhandari, “A Hybrid approach to Image Enhancement using Contrast Stretching on Image Sharpening and the analysis of various cases arising using Histogram,” International Conference on Recent Advances and Innovations in Engineering, pp.1-6, 2014.
• 7. Seyed Pooya Ehsani, Hojjat Sayed Mousavi, Babak. H. Khalaj, “Chromosome Image Contrast Enhancement Using Adaptive, Iterative Histogram Matching,” 7th Iranian Conference on Machine Vision and Image Processing, pp.8-771, 2011.
• 8. Che-Lun Hung, Ren-You Yan, Hsiao-His Wang, “ Parallel image dehazing algorithm based on GPU using fuzzy system and hybrid evolution algorithm,” 17th IEEE, pp.2-129, 2016.
• 9. Kwang Yeon Choi, Kyeong Min Jeong, Byung Cheol Song, “Fog detection for de-fogging of road driving images,” IEEE 20th International Conference on Intelligent Transportation Systems, pp.5-278, 2017.
• 10. Khairunnisa Hasikin, Nor Ashidi Mat Isa, “Enhancement of the low contrast image using fuzzy set theory,” 2012 UKSim 14th International Conference on Computing Modelling and Simulation, pp.26-1010, 2012.
• 11. Raju, Ganesamoorthy, Madhu S. Nair, “A new fuzzy-based decision algorithm for high-density impulse noise removal,” pp. 1-17, 2010.
• 12. Dong-Liang Peng, Tie-Jun Wu, “A generalized image enhancement algorithm using fuzzy sets and its application,” Proceedings. International Conference on Machine Learning and Cybernetics, pp.13-340, 2002.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).

Identyfikatory

DOI

10.15439/2020KM43