Academic Journal of Computing & Information Science, 2022, 5(6); doi: 10.25236/AJCIS.2022.050608.
Xuan Ren1, Songning Lai2
1School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Yangpu, Shanghai, 200093, China
2School of Information Science and Engineering, Shangdong University, No.72 Binhai Road, Jimo District, Qingdao, Shandong, 266000, China
Medical image enhancement is one of the most widely used medical image processing techniques in medical domain. Its purpose is to improve the visual effect of the image and facilitate the analysis and understanding of the image by human or machine. The Laplace transform and the Sobel gradient operator are two common ways of performing edge detection, image sharpening and enabling the image to be enhanced. However, each has limitations when used in isolation. The Laplace operator has a good edge detection effect, but it will make the image noise expand; the Sobel operator has a certain ability to smooth the noise, but the edges of the image obtained after processing are rougher. This paper therefore proposes a method based on both Laplace transform and Sobel operator, and histogram equalization of the transformed image is processed to enhance the image. Using a combination of both filtering methods avoids the disadvantage. This method was found to be effective in improving the quality of lung images and skeletal images through several experiments.
Medical image enhancement, Laplace transformation, Sobel operator, Histogram equalization
Xuan Ren, Songning Lai. Medical Image Enhancement Based on Laplace Transform, Sobel Operator and Histogram Equalization. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 6: 48-54. https://doi.org/10.25236/AJCIS.2022.050608.
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