HISTOGRAM EQUALIZATION BASED IMAGE ENHANCEMENT FOR MEDICAL IMAGE PROCESSING
DOI:
https://doi.org/10.61841/b7yeay86Keywords:
BPDHE algorithm, MRI image,, image enhancementAbstract
In the medical field, resonance imaging (MRI) is one of the advanced techniques, which can be used to provide rich data regarding the human body. Tomography of the medical image may be a useful tool to help physicians to diagnose. Bar chart exploits are among the required steps within the image sweetening methods for Medical images. There are different ways of image sweetening, every one of them is required for a special sort of analysis. In this paper, Brightness preserving Dynamic Histogram Equalization (BPDHE) used for image enhancement. Contrast-enhanced is that the digital manipulating dispensed to increase excellence and reduces the noise in digital imaging.
Downloads
References
1. A. Laine, J. Fan, and W. Yang, “Wavelets for contrast enhancement of digital mammography,” IEEE Eng. Med. Biol. Mag., vol. 14, no. 6, pp. 536–550, 1995.
2. W. Qian, L. P. Clarke, B. Zheng, M. Kallergi, and R. Clark, “Computer assisted diagnosis for digital mammography,” IEEE Eng. Med. Biol. Mag., vol. 14, no. 6, pp. 561–568, 1995.
3. A. N. Netravali and B. G. Haskeli, Digital Pictures: Representation and Compression. New York: Plenum, 1988, ch. 4.
4. R. C. Gonzalez and R. E. Woods, Digital Image Processing. New York: Addison-Wesley, 1992. [5] M. A. Sid-Ahmed, Image Processing: Theory, Algorithms, and Architectures. New York: McGraw-Hill, 1995, ch. 4.
5. J. D. Fahnestock and R. A. Schowengerdt, “Spatially variant contrast enhancement using local range modification,” Opt. Eng., vol. 22, no. 3, pp. 378–381, 1983.
6. I. Altas, J. Louis, and J. Belward, “A variational approach to the radiometric enhancement of digital imagery,” IEEE Trans. Image Processing, vol. 4, pp. 845–849, June 1995.
7. V.Velusamy, Dr. M. Karnan, Dr. R. Sivakumar, Dr.N. Nandhagopal, “Enhancement Techniques and Methods for MRI A Review”, International Journal of Computer Science and Information Technologies, Vol. 5 (1), pp .397-403, 2014.
8. R. H. Sherrir and G. A. Johnson, “Regionally adaptive histogram equalization of the chest,” IEEE Trans. Med. Imag., vol. MI-6, pp. 1–7, Jan. 1987.
9. S. M. Pizer, J. B. Zimmerman, and E. V. Staab, “Adaptive grey level assignment in CT scan display,” J. Comput. Assist. Tomogr., vol. 8, no. 2, pp. 300–305, 1984.
10. S. M. Pizer, E. P. Amburn, J. D. Austin, R. Cromartie, A. Geselowitz, T. Greer, B. H. Romeny, J. B. Zimmerman, and K. Zuiderveld, “Adaptive histogram equalization and its variations,” Comput. Vision, Graphics, Image Processing, vol. 39, pp. 355–368, 1987.
11. Md. Foisal Hossain, Mohammad Reza Alsharif, “Image Enhancement Based on Logarithmic Transform Coefficient and Adaptive Histogram Equalization”, 2007 International Conference on Convergence Information Technology, IEEE 2007.
12. K.Rajiv Gandhi, N.Nandhagopal, R.Sivasubramanian, “AutomaticSystem For Pre-Processing And Enhancement Of Magnetic Resonance Image (MRI)”,International Journal of Applied Engineering Research (IJAER)vol.9 (22),pp. 15485-15499,2014.
13. J. Alex Stark “Adaptive Image Contrast Enhancement Using Generalizations of Histogram Equalization”, IEEETransactions on ImageProcessing, Vol. 9, No. 5, May 2000.
14. Wang Yuanji. Li Jianhua, Lu E, Fu Yao, Jiang Qinzhong, “Image Quality Evaluation Based On Image Weighted Separating Block Peak Signal To Noise Ratio”, IEEE Int.Conf. Neural Networks &Signal Processing, Nanjing, China, December 14-17, 2003.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.