Contrast Enhancement of Power Plant Images Obtained from Industrial Borescope Devices

ammar, Reda; elsafrawey, Amir; ashiba, Huda; el-shafai, Waleed; elazm, Atef abou; samie, Fathi abd el

doi:10.21608/mjeer.2020.69191

	Contrast Enhancement of Power Plant Images Obtained from Industrial Borescope Devices
Menoufia Journal of Electronic Engineering Research
Article 13, Volume 29, Issue 1, January 2020, Page 91-97 PDF (1.12 MB)
Document Type: Original Article
DOI: 10.21608/mjeer.2020.69191
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Authors
Reda ammar¹; Amir elsafrawey²; Huda ashiba¹; Waleed el-shafai¹; Atef abou elazm²; Fathi abd el samie¹
¹Dept. of Electronics and Electrical Communications Engineering., Faculty of Elect., Eng., Menoufia University, Egypt.
²Dept. of Electronics and Electrical Communications Engineering., Faculty of Elect., Eng., Menoufia University, Egypt
Abstract
The industrial Video scope (VS) device is designed for the endoscopic inspection of professional equipment, like motors, pumps, turbines, cavities in buildings and vehicle bodies, etc. The output of this device is images and videos, but some output images may suffer from low contrast and poor details. This paper presents three proposed approaches to enhance the quality of the VS images. The first proposed approach is based on Contrast Limited Adaptive Histogram Equalization (CLAHE) with adaptive gamma correction. By choosing the best clip limits in CLAHE and transfer function (adaptive gamma correction), the first proposal achieves optimum contrast enhancement for the VS images. The second proposed approach depends on the Homomorphic with emphasis high pass filter. The homomorphic filtering is utilized on the video scope image in logarithm domain, Applying this method gives more details in the VS images. The third proposed approach depends on Homomorphic with emphasis high pass filter with histogram equalization. Applying this method gives more accurate and best visual quality of the output VS images. Numerical results show the ability of the three proposals in improvement the VS image quality, and they can be recommended for industrial VS systems.
Keywords
Videoscope images; CLAHE; Homomorphic filtering; adaptive gamma correction; Histogram equalization


References
[1] KARL STORZ, "Manual videoscope", GmbH & Co. KG, 2009. [2] h. Lidong, Z. Wei, W. Jun and S Zebin, "Combination of contrast limited adaptive histogram equalization and discrete wavelet transform for image enhancement", 2015. [3] R. Gonzalez and R. Woods, "Digital Image Processing", Vol. 3. London: Pearson Education, 2009. [4] C. Shih, C. Fan and S. Yi, "Efficient Contrast Enhancement Using Adaptive Gamma Correction with Weighting Distribution", 2013. [5] H. I. Ashiba, H. M. Mansour,H. M. Ahmed, M. I. Dessouky, M. F. El- Kordy, O. Zahran & Fathi E. Abd El-Samie, "Enhancement of IR images using histogram processing and the Undecimated additive wavelet transform", Multimedia Tools and Applications, doi.org/10.1007/s11042-018-6545-9, 2018. [6] R. Greg, B. Mitta and S. Grag, "Histogram equalization techniques for image enhancement", International Journal of Electronics & Communication Technology, 2(1), 107–111, 2011. [7] A. Singh, "Contrast Enhancement for Cephalometric Images using Wavelet-based Modified Adaptive Histogram Equalization", Soft Computing Journal, doi.org/doi:10.1016/j.asoc.2016.11.046,2016,2016. [8] K.Akilaa, L.S.Jayashreeb, A.Vasukic," Mammographic image enhancement using indirect contrast enhancement techniques – A comparative study ",Elsevier Procedia Computer Science, 2015. [9] S. Sophoan," Color Image Enhancement by Using Dynamic Piecewise Linear Transformation",sophoan.s-sse2018@tggs.kmutnb.ac.th,2018. [10] S.-D. Chen and A.- R. Ramli, "Minimum mean brightness error bi-histogram equalization in contrast enhancement”, IEEE Transactions on Consumer Electronics, November, 2003. [11] S.-D. Chen and A.-R. Ramli, "Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation”, IEEE Transactions on Consumer Electronics, 2003. [12] Y. Hel, H. Hel and E. David, "Fast template matching in non-linear tone-mapped images", In Computer vision (ICCV), international conference on IEEE (pp. 1355–1362), 2011. [13] J.-C Russ "The image processing handbook", (5rd edn.). CRC Press, 2007. [14] J.-P Rolland, V. Vo, B. Bloss and C.-K Abbey. "Fast algorithms for histogram matching: Application to texture synthesis", Journal of Electronic Imaging, 2000. [15] H.-I Ashiba, H.-M Mansour, H.-M Ahmed, M.-F El-Kordy, M.-I Dessouky and F.-E.-A. El-Samie, "Enhancement of infrared images based on efficient histogram processing", Multimedia Tools and Applications, https://doi.org/10.1007/s11277-017-4958-9, 2018. [16] S.-K Shame and S.-R.-K Vadali, "Enhancement of Di-abetic retinopathy imagery using contrast limited adaptive histogram equalization", International Journal of Computer Science and Information Technologies, 2(6), 2694–2699, 2011. [17] J.A Stark, "Adaptive image contrast enhancement using generalizations of histogram equalization", IEEE Transactions on Image Processing, 9(5), 889–894.doi: https://doi.org/10.1109 /83.841534, 2000. [18] W. Zhiming and T.- A Jianhua, "Fast implementation of adaptive histogram equalization", In IEEE, ICSP proceedings, 2006. [19] R. Gonzalez and R. Woods, "Digital Image Processing", 2nd edition, Upper Saddle River, 2001. [20] R. Gonzalez, R. Woods and S. Eddins, "Digital Image Processing Using MATLAB", 2004. [21] R. Gonzalez and R. Woods and S. Eddins, "Digital image processing using MATLAB", 2009. [22] T. T. Neo, "Fusion of Night Vision and Thermal Images', M.Sc. Thesis, Naval Postgraduate School, Universityof New South Wales, Australia, 2006 [23] S. Yin, L. Cao, Q. Tan, and G. Jin, "Infrared and Visibl Image Fusion based on NSCT and Fuzzy Logic ", in Proc. of the IEEE Int. Conf. on Mechatronics and Automation, pp. 671-675, August 4-7, 2010. [24] J. Zhuqing, "Study of Multi-Source Image Fusion Method in Transform Domain", 2011.
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