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SIAM J. Imaging Sci. 5, pp. 1-32 (32 pages)
Image Denoising Using Mean Curvature of Image Surface
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Add to FacebookWe propose a new variational model for image denoising, which employs the $L^{1}$-norm of the mean curvature of the image surface $(x,f(x))$ of a given image $f:\Omega\rightarrow\mathbb{R}$. Besides eliminating noise and preserving edges of objects efficiently, our model can keep corners of objects and greyscale intensity contrasts of images and also remove the staircase effect. In this paper, we analytically study the proposed model and justify why our model can preserve object corners and image contrasts. We apply the proposed model to the denoising of curves and plane images, and also compare the results with those obtained by using the classical Rudin–Osher–Fatemi model [Phys. D, 60 (1992), pp. 259–268].
© 2012 Society for Industrial and Applied Mathematics
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Received January 26, 2011
Accepted October 24, 2011
Published online January 17, 2012
Accepted October 24, 2011
Published online January 17, 2012
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