De-Noising of Corrupted Fluoroscopy Images Based on a New Multi-Line Algorithm

  • Maytham. A. Ali Department of Computer Techniques Engineering, Baghdad College of Economic Sciences University, Baghdad, Baghdad, Iraq
  • Rohaida Romli School of computing/ College of Arts and Sciences, Universiti Utara Malaysia, Kedah, Malaysia
Keywords: black and white type noise, de-noising high densities, fluoroscopy images, Multi-Line algorithm, corrupted images


 Fluoroscopic images are a field of medical images that depends on the quality of image for correct diagnosis; the main trouble is the de-nosing and how to keep the poise between degradation of noisy image, from one side, and edge and fine details preservation, from the other side, especially when fluoroscopic images contain black and white type noise with high density. The previous filters could usually handle low/medium black and white type noise densities, that expense edge, =fine details preservation and fail with high density of noise that corrupts the images. Therefore, this paper proposed a new Multi-Line algorithm that deals with high-corrupted image with high density of black and white type noise. The experiments achieved images with a high quality and effectively preserved edge and fine details against black and white type noise densities depending on Peak Signal to Noise Ratio (PSNR), Mean Squared Error (MSE), and Image Enhancement Factor (IEF) measures.

How to Cite
Ali, M. A., & Romli, R. (2020). De-Noising of Corrupted Fluoroscopy Images Based on a New Multi-Line Algorithm. Iraqi Journal of Science, 61(8), 2126-2131.
Computer Science