%0 Journal Article
%T Image Noise Reduction via Complex Diffusion
%A Bekir Dizdaro£¿lu
%J -
%D 2018
%X In this study, improved complex diffusion approaches are proposed for eliminating Gaussian noise in the input image. In the complex diffusion, meanwhile, the real component behaves as a low pass filter and the imaginary component behaves as a high pass filter. Thus, while the filter in the real component reduces the noise in the image, the filter in the imaginary component protects the structure information of the image. In the proposed methods, the fidelity term is used in the heat equation approach, where the linear diffusion is taken into account and operations is isotopically performed, and in the Perona-Malik approach, where the nonlinear diffusion is considered, addition to the regularization term. The fidelity term better preserves the structure information of the resulting image. On the other hand, the noise standard deviation is semi-automatically estimated, the Lagrange multiplier in the fidelity term is also optimized in each iteration and thus the additive noise reduction performance in the input image is improved via complex diffusion approaches. This performance in the proposed methods is supported by both qualitative and quantitative results when the noise standard deviation is not too high
%K G¨¹r¨¹lt¨¹ azaltma
%K karma£¿£¿k yay£¿n£¿m
%K £¿s£¿ denklemi
%K Perona-Malik yakla£¿£¿m£¿
%K d¨¹zenlile£¿tirme ve uygunluk terimleri
%K Lagrange £¿arpan£¿
%U http://dergipark.org.tr/erciyesfen/issue/37078/407438