ANALISIS KINERJA NOISE FILTERING UNTUK MENGHILANGKAN DERAU PADA CITRA SEDIAAN DARAH TIPIS MALARIA - Setyawan, Doni; Sulistyowati, Istri; Suradi, Agustinus; Rizqita Nur Rahma, Vina (Journal of Computer Science and Technology (JCS-TECH), 2025)
In automated malaria diagnosis systems, the images resulting from the acquisition process may contain noise, which can obscure the visual appearance of the Plasmodium. Therefore, noise filtering techniques are needed to remove noise from the images. This study evaluates the performance of noise filtering techniques under various noise conditions to determine the most effective method for removing noise in blood smear images.The research consists of several stages: acquisition of thin blood smear images, noise addition, noise filtering, and performance comparison of the noise filtering methods. The image acquisition was carried out using the publicly available MP-IDB malaria dataset. Noise addition was performed using salt and pepper, Gaussian, and mixed noise. The tested noise filtering techniques include median filtering, Gaussian filtering, and average filtering. The performance of the noise filtering methods was assessed using Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) measurements.The experimental results show that for blood smear images with salt and pepper noise, the median filtering method provided the best results with an MSE of 6.51 and a PSNR of 43.13. Visually, the noise-removed image using median filtering closely resembled the original image. For images with Gaussian noise, the average filtering method achieved the best performance with an MSE of 31.81 and a PSNR of 33.19. For images with mixed noise, the median filtering method again provided the best performance with an MSE of 46.95 and a PSNR of 31.46.