Indian Journal of Science and Technology
Year: 2023, Volume: 16, Issue: 32, Pages: 2534-2539
Original Article
K Kannan1*, S Arumuga Perumal2
1Department of Mechatronics Engineering, KAMARAJ College of Engg & Tech, K. Vellkulam , 625701, India
2Department of Computer Science, S.T. Hindu College, Nagarcoil, 629001, India
*Corresponding Author
Email: [email protected]
Received Date:31 March 2023, Accepted Date:19 July 2023, Published Date:28 August 2023
Objective: The main objective of this study is to enhance the contrast and edge information present in the Proton density magnetic resonance medical images to increase the perception of information and provide better visualization format for effective diagnostics and treatment. Method: In the proposed algorithm, adaptive histogram equalization is applied to the input proton density magnetic resonance image to enhance the contrast followed by the unsharp mask filtering to improve the high frequency edge information of the image. Four proton density magnetic resonance images were downloaded from the dataset available in National Library of Medicine website, the experiment was carried out by writing the MATLAB code and executed by Intel Pentium Processor CPU4417U @ 2.3 GHz. Findings: Results reveal that the proposed method out performs adaptive histogram equalization (AHE) technique and Classical Unsharp Masking Filter (CUMF) both in terms of visual quality along with edge preservation and contrast enhancement. The quality of output image from the proposed method is enhanced by 1.34 times over AHE & 1.88 times over CUMF in terms of Spatial Frequency and 1.33 times over AHE & 2.18 times over CUMF in terms of Sharpness. Novelty: This study combines both histogram equalization and unsharp masking to enhance both contrast and edge information of proton density magnetic resonance medical images for effective diagnostics and treatment.
Keywords: Proton Density Magnetic Resonance Images; Medical Image Enhancement; Unsharp Mask Filter; Histogram Equalization; Spatial Frequency; Mean Gradient; Sharpness
© 2023 Kannan & Perumal. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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