Image Enhancement of Medical Images Based on an Efficient Approach of Morphological and Arithmetic Operations

International Journal of Computer Trends and Technology (IJCTT)          
© 2017 by IJCTT Journal
Volume-49 Number-5
Year of Publication : 2017
Authors : Usha Ramasamy, Perumal K


Usha Ramasamy, Perumal K "Image Enhancement of Medical Images Based on an Efficient Approach of Morphological and Arithmetic Operations". International Journal of Computer Trends and Technology (IJCTT) V49(5):253-258, July 2017. ISSN:2231-2803. Published by Seventh Sense Research Group.

Abstract -
This paper presents a new approach for a medical image pre-processing and enhancing to further segmentation and classification. An idea of this technique is helpful to improve the image contrast and quality as well as to extract if any abnormal part in a brain image. Then the size of structuring element choice, top-hat, bottom-hat morphological operation and some arithmetic operation are used for an image enhancement to increase the image contrast and quality. And image complement operation has incorporated with this process for separate the abnormal tissues from enhanced image when it is needed. The choice of the best size of structuring element in the disk-shaped mask is helpful to increase the image contrast as well as improves the Correct Classification Rate or accuracy for MRI brain-image diagnosis.

[1] D. Jude Hemanth and J. Anitha, “Image Pre-processing and Feature Extraction Techniques for Magnetic Resonance Brain Image Analysis”, Computer Applications for Communications, Networking, and Digital Contents, Communications in Computer and Information Science, Vol.350, pp.349-356, © Springer-Verlag Berlin, Heidelberg, Jan 2012.
[2] Y. Yang, Z. Su, and L. Sun, “Medical Image Enhancement Algorithm Based on Wavelet Transform”, IEEE Electronics Letters, Vol.46, pp.120-121, Jan 2010.
[3] C.J. Moore, “Medical Image Processing: The Characterization of Display Changes Using Histogram Entropy”, Image and Vision and Computing, Vol.4, pp.197-202, 1986.
[4] Qian Wang, Liya Chen, and Dinggang Shen, “Fast Histogram Equalization for Medical Image Enhancement”, Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vancouver, British Columbia, Canada, pp.2217-2220, 20-24 Aug 2008.
[5] N. Sengee, B. Bazarragchaa, K. Tae Yun, and C. Heung Kook, “Weight Clustering Histogram Equalization for Medical Image Enhancement”, Proceedings of the IEEE International Conference on Communications Workshops, Honolulu, Hawaii, USA, 1-5, pp.14-18 June 2009.
[6] J.C. Fu, H.C. Lien, and S.T.C. Wong, “Wavelet-based Histogram Equalization Enhancement of Gastric Sonogram Images”, Computerized Medical Imaging and Graphics, 24.pp.59-68, Jan 2000.
[7] S. Asadi Amiri, and H. Hassanpour, “A Preprocessing Approach for Image Analysis Using Gamma Correction”, International Journal of Computer Applications, vol.38-No.12, pp.38-46, Jan 2012.
[8] Petros Maragos, “Differential Morphology and Image Processing”, IEEE Transactions on Image Processing, Vol.5, No.6, pp.922-937, June 1996.
[9] F. Oritz, and F. Torres, “Vectorial Morphological Reconstruction for Brightness Elimination in Colour Images”, ELSEVIER, Real-Time Imaging, Vol.10, pp.379-387, Dec 2004.
[10] X.-J. Jing, N. Yu, and Y. Shang, “Image Filtering Based on Mathematical Morphology and Visual Perception Principle”, Chinese Journal of Electronics, Vol.13, pp.612-616, 2004.
[11] Richard Alan Peters, “A New Algorithm for Image Noise Reduction using Mathematical Morphology”, IEEE Transaction on Image Processing, Vol.4, pp.554-568, May 1995.
[12] A. Mahmoud Tarek, and Marshall Stephen., “Medical Image Enhancement Using Threshold Decomposition Driven Adaptive Morphological Filter”, Proceedings of the 16th European Signal Processing Conference, Lausanne, Switzerland, pp. 25-29 Aug 2008.
[13] T. Chen, Q.H. Wu, R. Rahmani-Torkaman, and J. Hughes, “A Pseudo Top-Hat Mathematical Morphological Approach to Edge Detection in Dark Regions”, PERGAMON, Pattern Recognition, 35, pp.199-210, 2002.
[14] J. Serra, “Image Analysis and Mathematical Morphology”, Academic Press, New York, 1982.
[15] Suman Thapar, and Shevani Garg, “Study and Implementation of Various Morphology Based Image Contrast Enhancement Techniques”, International Journal of Computing and Business Research, Proceedings of „I-Society 2012‟, 2229-6166, 2012.
[16] R. Gonzalez and R. Woods, “Digital Image Processing”, 2nd edition. Prentice Hall, Jan 2002.
[17] Jean-Luc Starck, Emmanue J. Candes, and David L. Donoho, “The Curvlet Transform for Image Denoising”, IEEE Transactions on Image Processing, Vol.11, No.6, June 2002.

Magnetic Resonance Image, Morphological operations, Top hat transform, Bottom hat transform, Image Enhancement.