Abstract
In this work, we use partial differential equation techniques to remove noise from digital images. The removal is done in two steps. We first use a total-variation filter to smooth the normal vectors of the level curves of a noise image. After this, we try to find a surface to fit the smoothed normal vectors. For each of these two stages, the problem is reduced to a nonlinear partial differential equation. Finite difference schemes are used to solve these equations. A broad range of numerical examples are given in the paper.
Publication types
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Comparative Study
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Evaluation Study
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Research Support, Non-U.S. Gov't
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Research Support, U.S. Gov't, Non-P.H.S.
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Validation Study
MeSH terms
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Algorithms*
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Cluster Analysis
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Computer Simulation
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Image Enhancement / methods*
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Image Interpretation, Computer-Assisted / methods*
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Imaging, Three-Dimensional / methods
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Information Storage and Retrieval / methods*
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Models, Statistical
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Numerical Analysis, Computer-Assisted*
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Pattern Recognition, Automated*
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Reproducibility of Results
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Sensitivity and Specificity
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Signal Processing, Computer-Assisted
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Stochastic Processes
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Subtraction Technique*