Pengaruh Filter Lowpass Terhadap Kualitas Citra CT-Scan Paru-Paru - Sofhia Ulga; Afdhal Muttaqin; Dian Fitriyani (Universitas Andalas, 2024)
A low pass filter can be employed to enhance the quality of lung CT-Scan images by smoothing sharp transitions and reducing noise present in the images. The aim of this research is to implement a low pass filter by applying different weight values. The kernel weights applied in filtering using a low pass filter are 1/6, 1/9, 1/10, and 1/16. This study is a quantitative research employing 102 images. The findings of this study reveal that applying low pass filters with different kernel weights yields varying image qualities. Based on the quality tests of Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR), it was found that the kernel weight of 1/6 produces images with excellent quality at 17,65%, good quality at 28,93%, and fair quality at 53,92%. Meanwhile, with a kernel weight of the 1/9, 36,36% of the images were found to have good quality, while 64% exhibited lower quality. The application of a low pass filter with a kernel weight of 1/10 resulted in 39% of the images being of good quality and 61% of the images being of lower quality. At the kernel weight of 1/16, 2% of the images were obtained with excellent quality, 40% with good quality, and 58% with lower quality. Based on the MSE and PSNR test values, it was found that applying a kernel weight of 1/6 resulted in better image quality compared to applying other kernel weights. From the overall result, it was found that the application of a low pass filter was not suitable for improving the quality of CT-Scan images of the lung, so other methods could be applied to improve the quality of the images.