Analisis Perbandingan Algoritme Penghapusan Noise pada Citra X-Ray Paru-Paru

Tjahjadi, Jhonatan Laurensius and Tanuwijaya, Padmavati Darma Putri and Riti, Yosefina Finsensia (2023) Analisis Perbandingan Algoritme Penghapusan Noise pada Citra X-Ray Paru-Paru. Jurnal Pseudocode, 10 (2). pp. 80-89. ISSN 2355-5920 | e-2655-1845

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Abstract

Pulmonary X-ray is a medical diagnostic method used to produce internal lung images. However, the X-ray process is often interrupted when capturing images, resulting in noisy image results. This condition diminishes the clarity of information contained in the lung X-ray images. Therefore, noise removal or denoising is essential. Denoising is a fundamental image processing technique aimed at improving image quality for optimal information transmission. This study applies denoising methods to 20 datasets of pulmonary X-ray images using Median, Mean, Gaussian, Bilateral, and Wiener filters, with Python and the OpenCV Library. Error measurement for noise filtering is conducted using Peak Signal-to-Noise Ratio and Mean Square Error methods. The research results show that the median filter stands out as an excellent denoising method, outperforming others with a Peak Signal-to-Noise Ratio of 37.6444 and a Mean Square Error of 11.3339 for Salt and Pepper Noise.

Item Type:	Article
Uncontrolled Keywords:	Denoising; Filtering; MSE; PSNR; X-Ray
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Prodi Ilmu Informatika
Depositing User:	Yosefina Finsensia Riti
Date Deposited:	10 Mar 2025 02:37
Last Modified:	11 Mar 2025 07:42
URI:	http://repositori.ukdc.ac.id/id/eprint/2172

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