A METHOD FOR IMAGE DE-NOISING BASED ON ANISOTROPIC DIFFUSION - M. Rohitha, E.G Geetha Laxmi & V. Janardhan Babu (International Journal of Research Science and Management, 2017)
The image may be corrupted by random variations in intensity, variations in illumination, or poor contrast that must be dealt with in the early stages of vision processing. In the existing method a weighted guided image filter is introduced by incorporating an edge-aware weighting into a guided image filter to address the problem. This paper provides the derivation of noise reducing anisotropic diffusion, a diffusion method tailored to imaging applications. Anisotropic diffusion can be used to remove noise from digital images without blurring edges. With a constant diffusion coefficient, the anisotropic diffusion equations reduce to the heat equation which is equivalent to Gaussian blurring. The experimental results show that the proposed method is better compare to the state of art of criteria.