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Nonlinear Scale Space with Spatially Varying Stopping Time
December 2008 (vol. 30 no. 12)
pp. 2175-2187
A general scale space algorithm is presented for denoising signals and images with spatially varying dominant scales. The process is formulated as a partial differential equation with spatially varying time. The proposed adaptivity is semi-local and is in conjunction with the classical gradient-based diffusion coefficient, designed to preserve edges. The new algorithm aims at maximizing a local SNR measure of the denoised image. It is based on a generalization of a global stopping time criterion presented recently by the author and colleagues. Most notably, the method works well also for partially textured images and outperforms any selection of a global stopping time. Given an estimate of the noise variance, the procedure is automatic and can be applied well to most natural images.

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Index Terms:
Smoothing, Parabolic equations, Partial Differential Equations
Citation:
Guy Gilboa, "Nonlinear Scale Space with Spatially Varying Stopping Time," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 12, pp. 2175-2187, Dec. 2008, doi:10.1109/TPAMI.2008.23
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