Visibility Enhancement for Images Captured in Dusty Weather via Tuned Tri-threshold Fuzzy Intensification Operators

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Zohair Al-Ameen 1,*

1. Department of General Education, College of Education and Languages, Lebanese French University, Erbil, Iraq

* Corresponding author.


Received: 1 Nov. 2015 / Revised: 11 Feb. 2016 / Accepted: 27 Apr. 2016 / Published: 8 Aug. 2016

Index Terms

Color cast, Color image enhancement, Degraded image, Dusty weather, Fuzzy intensification operators


An inclement dusty weather can significantly reduce the visual quality of captured images and this consequently leads to hamper the observation of meaningful image details. Capturing images in such weather often leads to undesirable artifacts such as poor contrast, deficient colors or color cast. Hence, various methods have been proposed to process such unwanted event and recover vivid results with acceptable colors. These methods vary from simple to complex due to the variation of the used processing concepts. In this article, an innovative technique that utilizes tuned fuzzy intensification operators is introduced to expeditiously process poor quality images captured in an inclement dusty weather. Intensive experiments were carried out to check the processing ability of the proposed technique, wherein the obtained results exhibited its competence in filtering various degraded images. Specifically, it performed well in providing acceptable colors and unveiling fine details for the processed images.

Cite This Paper

Zohair Al-Ameen, "Visibility Enhancement for Images Captured in Dusty Weather via Tuned Tri-threshold Fuzzy Intensification Operators", International Journal of Intelligent Systems and Applications (IJISA), Vol.8, No.8, pp.10-17, 2016. DOI:10.5815/ijisa.2016.08.02


[1]T. Yan, L. Wang and J. Wang, "Method to Enhance Degraded Image in Dust Environment", Journal of Software, vol. 9, no. 10, pp. 2672- 2677, 2014.
[2]S. Narasimhan and S. Nayar, "Contrast restoration of weather degraded images", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 6, pp. 713-724, 2003.
[3]S. Huang, J. Ye and B. Chen, "An Advanced Single-Image Visibility Restoration Algorithm for Real-World Hazy Scenes", IEEE Transactions on Industrial Electronics, vol. 62, no. 5, pp. 2962-2972, 2015.
[4]B. Chen and S. Huang, "An Advanced Visibility Restoration Algorithm for Single Hazy Images", ACM Transactions on Multimedia Computing, Communications, and Applications, vol. 11, no. 4, pp. 1-21, 2015.
[5]S. Huang, "An Advanced Motion Detection Algorithm With Video Quality Analysis for Video Surveillance Systems", IEEE Transactions on Circuits and Systems for Video Technology, vol. 21, no. 1, pp. 1-14, 2011.
[6]S. C. Huang, B. H. Chen, and Y. J. Cheng, “An efficient visibility enhancement algorithm for road scenes captured by intelligent transportation systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 5, pp. 2321–2332, 2014.
[7]S. C. Huang and B. H. Do, “Radial basis function based neural network for motion detection in dynamic scenes,” IEEE Transactions on Cybernetics, vol. 44, no. 1, pp. 114–125, 2014.
[8]M. Chacon and S. Gonzalez, “An adaptive neural-fuzzy approach for object detection in dynamic backgrounds for surveillance systems,” IEEE Transactions on Industrial Electronics, vol. 59, no. 8, pp. 3286–3298, 2012.
[9]X. Zhang, W. Hu, S. Chen, and S. Maybank, “Graph-embedding-based learning for robust object tracking,” IEEE Transactions on Industrial Electronics, vol. 61, no. 2, pp. 1072–1084, 2014.
[10]K. Kaur and N. Gupta, "Performance Evaluation of Modified DBLA Using Dark Channel Prior & CLAHE", International Journal of Intelligent Systems and Applications, vol. 7, no. 5, pp. 48-56, 2015.
[11]J. Wang, Y. Pang, Y. He, and Changshu Liu. "Enhancement for Dust-Sand Storm Images." In Lecture Notes in Computer Science (MultiMedia Modeling), Vol. 9516, Q. Tian, N. Sebe, G. Qi, B. Huet, R. Hong and X. Liu, Eds. Springer International Publishing, 2016, pp. 842-849.
[12]A. Mohamad, "A New Image Contrast Enhancement in Fuzzy Property Domain Plane for a True Color Images", International Journal of Signal Processing Systems, vol. 4, no. 1, 45-50, 2016.
[13]A. Łoza, D. Bull, P. Hill and A. Achim, "Automatic contrast enhancement of low-light images based on local statistics of wavelet coefficients", Digital Signal Processing, vol. 23, no. 6, pp. 1856-1866, 2013.
[14]M. Hanmandlu and D. Jha, "An Optimal Fuzzy System for Color Image Enhancement", IEEE Transactions on Image Processing, vol. 15, no. 10, pp. 2956-2966, 2006.
[15]T. Chaira, and A. Ray, Fuzzy image processing and applications with MATLAB, Boca Raton: CRC Press, 2009, pp. 49-50.
[16]S. Lam, A. Girardin and S. Srihari, “Gray-scale character recognition using boundary features”, Proceedings of SPIE 1661, Machine Vision Applications in Character Recognition and Industrial Inspection, vol. 98, February 09, 1992, San Jose, USA, pp. 98-105.
[17]N. Fang and M. Cheng, "An automatic crossover point selection technique for image enhancement using fuzzy sets", Pattern Recognition Letters, vol. 14, no. 5, pp. 397-406, 1993.
[18]W. Lei and Q. Feihu, "Adaptive fuzzy Kohonen clustering network for image segmentation", International Joint Conference on Neural Networks, vol. 4, 10 Jul 1999-16 Jul 1999, Washington, USA, pp. 2664-2667.
[19]M. Hanmandlu, D. Jha and R. Sharma, "Color image enhancement by fuzzy intensification", Pattern Recognition Letters, vol. 24, no. 1-3, pp. 81-87, 2003.
[20]C. Florea, A. Vlaicu, M. Gordan and B. Orza, "Fuzzy intensification operator based contrast enhancement in the compressed domain", Applied Soft Computing, vol. 9, no. 3, pp. 1139-1148, 2009.
[21]F. Sahba and A. Venetsanopoulos, "A novel fuzzy based framework for detection of clustered microcalcification in mammograms", IEEE International Conference on Fuzzy Systems, 18-23 July 2010, Barcelona, Spain, pp. 1-6.
[22]F. Sahba. “A new method for contour determination of the prostate in ultrasound images.” In Abdominal Imaging. Computational and Clinical Applications, H. Yoshida, G. Sakas and M. Linguraru, Eds. Springer Berlin Heidelberg, 2011, pp. 248-255.
[23]M. Yakno, J. Saleh and B. Rosdi. “Low contrast hand vein image enhancement”, IEEE International Conference on Signal and Image Processing Applications, 16-18 Nov. 2011, Kuala Lumpur, Malaysia, pp. 390-392.
[24]A. Kamalakannan and G. Rajamanickam, "High Performance Color Image Processing in Multicore CPU using MFC Multithreading", International Journal of Advanced Computer Science and Applications, vol. 4, no. 12, pp. 42-47, 2013.
[25]G. Sudhavani, K. Ram, P. Rao and K. Prasad, "Face Detection and Tracking in Fuzzy Enhanced Low Contrast Images", International Journal of Computer Applications, vol. 119, no. 16, pp. 31-35, 2015.