Abstract: Image de-noising is the elimination of noise from digital images where noise is any undesired information that contaminates an image. De-nosing is achieved through various filtering techniques that not only enhance the image but also keeps all its important details. Filters are categorized into linear (Geometric mean and Harmonic mean filters) and non-linear (midpoint, alpha-trimmed and adaptive local noise reduction filter) techniques. This paper presents applying Gaussian de-noising techniques or algorithms in spatial domain for medical images. Actually, five de-noising techniques are developed on gray scale medical images corrupted by additive Gaussian noise with mean = 0, variance = 1000. In addition, the paper analyzes the de-nosing techniques in terms of MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio) for image quality assessment and time complexity for performance assessment. The results showed that the de-nosing technique named Harmonic filter was the best from PSNR prospective and the de-nosing technique named Geometric mean filter was the best form time prospective.

Keywords: Gaussian noise elimination, Linear and non-linear filter

Link:

GAUSSIAN DE-NOSING TECHNIQUES IN SPATIAL DOMAIN FOR GRAY SCALE MEDICAL IMAGES

Nora Youssef, Abeer M.Mahmoud, El-Sayed? M.El-Horbaty

http://www.foibg.com/ijitk/ijitk-vol08/ijitk08-03-p09.pdf