| Autor: |
Khairi, Siti Shaliza Mohd, Bakar, Mohd Aftar Abu, Alias, Mohd Almie, Bakar, Sakhinah Abu |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3150 Issue 1, p1-7, 7p |
| Abstrakt: |
Medical images are images of the interior body taken using medical imaging techniques. Most of these images are contaminated with noise caused by transmission limitations or storage devices during the process of image collection from MRI, CT scan, or biopsy procedures. To date, many researchers have found that image denoising is a difficult task because they must strike a balance between noise reduction and preserving sharp image edges. Instead of conventional denoising methods, this paper studies the application of Shearlet transform for denoising the medical image. Shearlet transform is able to provide better directional determination during image reconstruction because it has the properties of a multiscale and is able to extract anisotropic features on images. In this study, different thresholding methods such as hard threshold, Otsu threshold and adaptive threshold were considered for denoising the image. In this study, peak signal-to-noise ratio (PSNR), mean square error (MSE) and structural similar index (SSIM) are used for performance evaluation. The experimental results show that the Shearlet transform is suitable to be used for denoising the medical images, where the most suitable thresholding method is the hard threshold, which it effectively reconstructs the images and preserve the edges on medical images compared to the other considered thresholding methods. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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