Noise removal or video sequences with ,3-D anisotropic diffusion equation
Seokho Lee, Eun-Cheol Choe, Mun-Gi Gang
Abstract
Seokho Lee, Eun-Cheol Choe, Mun-Gi Gang
Abstract
Nowadays there is a trend to apply the diffusion equation to image Processing. The anisotropic diffusion equation is highly favoured as a noise removal algorithm because it can remove noise while enhancing edges. However if the two dimensional anisotropic diffusion equation is applied to the noise removal of video sequences, flickering artifact due to the luminance difference between frames and ghost artifact due to the interfiltering between frames occur. In this paper the two dimensional anisotropic diffusion equation is extended to the sequence axis. The Proposed three dimensional anisotropic diffusion equation removes noise more efficiently than the two dimensional equation, and furthermore removes the flickering and ghost artifact as well.
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Nowadays there is a trend to apply the diffusion equation to image Processing. The anisotropic diffusion equation is highly favoured as a noise removal algorithm because it can remove noise while enhancing edges. However if the two dimensional anisotropic diffusion equation is applied to the noise removal of video sequences, flickering artifact due to the luminance difference between frames and ghost artifact due to the interfiltering between frames occur. In this paper the two dimensional anisotropic diffusion equation is extended to the sequence axis. The Proposed three dimensional anisotropic diffusion equation removes noise more efficiently than the two dimensional equation, and furthermore removes the flickering and ghost artifact as well.
Key concepts: Anisotropic diffusion, Diffusion equation, Artifact (error), Noise (video), Diffusion, Luminance, Anisotropy, Sequence (biology)