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Fuzzy Contrast Enhancement System with Multiple Transform Domain OperationsJAVID, T.![]() ![]() ![]() ![]() ![]() ![]() |
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Author keywords
Fourier transform, fuzzy systems, image enhancement, image fusion, wavelet transforms
References keywords
image(14), fuzzy(11), enhancement(8), medical(7), systems(6), fusion(6), processing(5), information(5), histogram(5), equalization(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2021-02-28
Volume 21, Issue 1, Year 2021, On page(s): 83 - 90
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.01009
Web of Science Accession Number: 000624018800009
SCOPUS ID: 85102794982
Abstract
Medical images provide an excellent way to identify the presence of diseases in a highly acceptable and correct manner. These images, however, due to the physical limitations of imaging instruments, have various types of artifacts. Techniques, such as those found in the computer-based image processing discipline are used as an alternative to the costly instrument to reduce or control these artifacts. A medical expert performs the complex task of disease identification and prognosis based on the visualized medical image data. The quality of medical images thus plays an important role to lower the chance of misdiagnosis and resulting in incorrect treatment. To meet the requirement of high-quality image data for the medical professional, in this research work, an innovative system is developed with the help of standard transform domain operations, data fusion, and fuzzy contrast enhancement system. Furthermore, the graphics processing unit and lookup table based technique are combined toward potential real-time implementation of the designed system. The proposed system can significantly improve the radiological contents inside medical image data to ease the task of the medical expert. |
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[1] R. C. Gonzalez, R. E. Woods. Digital image processing. New Jersey, USA: Pearson Prentice Hall, pp. 169-189, 2008.
[2] W. Y. Hsu, C. Y. Chou, "Medical image enhancement using modified color histogram equalization," Journal of Medical and Biological Engineering, vol. 35, pp. 580-584, 2015. [CrossRef] [Web of Science Times Cited 19] [SCOPUS Times Cited 29] [3] P. Kandhway, A. K. Bhandari, A. Singh, "A novel reformed histogram equalization based medical image contrast enhancement using krill herd optimization," Biomedical Signal Processing and Control, vol. 56, p. 101677, 2020. [CrossRef] [Web of Science Times Cited 46] [SCOPUS Times Cited 53] [4] S. Saravanan, R. Karthigaivel, "A fuzzy and spline based dynamic histogram equalization for contrast enhancement of brain images," International Journal of Imaging Systems and Technology, pp. 1-26, 2020. [CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 4] [5] L. Bai, W. Zhang, X. Pan, C. Zhao, "Underwater image enhancement based on global and local equalization of histogram and dual-image multi-scale fusion," IEEE Access, vol. 8, pp.128973-128990, 2020. [CrossRef] [Web of Science Times Cited 35] [SCOPUS Times Cited 50] [6] A. M. Pour, H. Seyedarabi, S. H. A. Jahromi, A. Javadzadeh, "Automatic detection and monitoring of diabetic retinopathy using efficient convolutional neural networks and contrast limited adaptive histogram equalization," IEEE Access, vol. 8, pp. 136668-136673, 2020, [CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 43] [7] L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, pp. 338-353, 1965. [CrossRef] [Web of Science Times Cited 49429] [SCOPUS Times Cited 61762] [8] L. A. Zadeh, "Outline of a new approach to the analysis of complex systems and decision processes," IEEE Trans. on Systems, Man, and Cybernetics, vol. SMC-3, pp. 28-44, 1973. [CrossRef] [Web of Science Times Cited 4694] [SCOPUS Times Cited 6240] [9] L. A. Zadeh, "A fuzzy-algorithmic approach to the definition of complex or imprecise concepts," International Journal of Man-Machine Studies, vol. 8, pp. 249-291, 1976. [CrossRef] [Web of Science Times Cited 348] [SCOPUS Times Cited 413] [10] K. P. Adlassnig, "Fuzzy set theory in medical diagnosis," IEEE Trans. on Systems, Man, and Cybernetics, vol. 16, pp. 260-265, 1986. [CrossRef] [Web of Science Times Cited 214] [SCOPUS Times Cited 296] [11] D. K. Iakovidis, E. Papageorgiou, "Intuitionistic fuzzy cognitive maps for medical decision making," IEEE Trans. on Information Technology in Biomedicine, vol. 15, pp. 100-107, 2010. [CrossRef] [Web of Science Times Cited 127] [SCOPUS Times Cited 155] [12] B. A. Akinnuwesi, B.A. Adegbite, F. Adelowo, U. Ima-Edomwonyi, G. Fashoto, O. T. Amumeji, "Decision support system for diagnosing rheumatic-musculoskeletal disease using fuzzy cognitive map technique," Informatics in Medicine Unlocked, vol. 18, p. 100279, 2020. [CrossRef] [SCOPUS Times Cited 18] [13] T. Javid, P. Akhtar, A. Dilshad, I. Mala, S. S. Zia, "Implementation of fuzzy rule-based contrast enhancement system," NED University Journal of Research, vol. Special Issue (ICONICS-2016), pp. 23-30, 2018. [14] S. Araghinejad. Data-driven modeling: Using MATLAB in water resources and environmental engineering. Dor-drecht, Netherlands: Springer, pp. 263-265, 2014. [15] S. Araghinejad, M. Azmi, M. Kholghi, "Application of artificial neural network ensembles in probabilistic hydrological forecasting," Journal of Hydrology, vol. 407, pp. 94-104, 2011. [CrossRef] [Web of Science Times Cited 48] [SCOPUS Times Cited 56] [16] D. L. Donoho, "Compressed sensing," IEEE Trans. Information Theory, vol. 52, pp. 1289-1306, 2006. [CrossRef] [Web of Science Times Cited 17857] [SCOPUS Times Cited 22543] [17] M. Lustig, D. Donoho, J. M. Pauly, "Sparse MRI: The application of compressed sensing for rapid MR imaging," Magnetic Resonance in Medicine, vol. 58, pp. 1182-1195, 2007. [CrossRef] [Web of Science Times Cited 4372] [SCOPUS Times Cited 4813] [18] S. Foucart, H. Rauhut. A mathematical introduction to compressive sensing. Bull. Am. Math, 54, pp. 151-165, 2017. [19] P. Akhtar, TJ. Ali, MI. Bhatti, M.A. Muqeet, "A Framework for Edge Detection and Linking Using Wavelets and Image Fusion," in Proc. IEEE Congress on Image and Signal Processing, Sanya, Hainan, China, 2008, pp. 273-277. [CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 7] [20] T. M. Cover, J. A. Thomas. Elements of information theory. Hoboken, New Jersey: John Wiley & Sons, p. 7, 2006. [21] T. Stathaki. Image fusion: Algorithms and applications. London, UK: Elsevier, p. 454, 2008. [22] C. Ramesh, T. Ranjith, "Fusion performance measures and a lifting wavelet transform based algorithm for image fusion," in Proc. 5th IEEE International Conference on Information Fusion, Annapolis, MD, USA, 2002, pp. 317-320. [CrossRef] [SCOPUS Times Cited 55] [23] L. Krasula, P. Callet, K. Fliegel, M. Klima, "Quality assessment of sharpened images: challenges, methodology, and objective metrics," IEEE Transaction on Image Processing, vol. 26, pp. 1496-1508, 2017. [CrossRef] [Web of Science Times Cited 36] [SCOPUS Times Cited 43] [24] I. Perfilieva, "Fuzzy transforms: Theory and applications," Fuzzy Sets and Systems, vol. 157, pp. 993-1023, 2006. [CrossRef] [Web of Science Times Cited 435] [SCOPUS Times Cited 492] [25] M. N. Do, M. Vetterli, "The contourlet transform: An efficient directional multiresolution image representation," IEEE Transactions on Image Processing, vol. 14, pp. 2091-2106, 2005. [CrossRef] [Web of Science Times Cited 2564] [SCOPUS Times Cited 3705] [26] Y. Fan, F. Xiao, "TDIFS: Two dimensional intuitionistic fuzzy sets," Engineering Applications of Artificial Intelligence, vol. 95, p. 103882, 2020. [CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 9] [27] H. Deng, W. Deng, X. Sun, M. Liu, C. Ye, X. Zhou, "Mammogram enhancement using intuitionistic fuzzy sets," IEEE Transactions on Biomedical Engineering, vol. 64, pp. 1803-1814, 2016. [CrossRef] [Web of Science Times Cited 19] [SCOPUS Times Cited 28] [28] Z. Li, Z. Jia, J. Yang, N. Kasabov, "An efficient and high quality medical CT image enhancement algorithm," International Journal of Imaging Systems and Technology, vol. 30, pp. 939-949, 2020. [CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 12] [29] X. Tian, J. Wang, D. Du, S. Li, C. Han, G. Zhu, Y. Tan, S. Ma, H. Chen, M. Lei, "Medical imaging and diagnosis of subpatellar vertebrae based on improved Laplacian image enhancement algorithm," Computer Methods and Programs in Biomedicine, vol. 187, p. 105082, 2020. 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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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