TotalVariationFilter

TotalVariationFilter[data]

iteratively reduces noise while preserving rapid transitions in data.

TotalVariationFilter[data,param]

assumes a regularization parameter value param.

Details and Options

  • TotalVariationFilter, also known as total variation regularization, is an iterative filter commonly used to reduce different types of additive or multiplicative noise while preserving sharp transitions.
  • In TotalVariationFilter[data,param], the value of regularization parameter param is typically in the range 0 to 1.
  • The data can be any of the following:
  • listarbitrary-rank numerical array
    tseriestemporal data such as TimeSeries, TemporalData,
    imagearbitrary Image or Image3D object
    audioan Audio object
  • The following options can be specified:
  • MaxIterations30maximum number of iterations to be performed
    Method"Gaussian"type of noise to be removed
  • Possible Method settings include: »
  • "Gaussian"additive Gaussian, uniform and other types of noise
    "Laplacian"salt-and-pepper or impulse noise
    "Poisson"multiplicative noise, as in low-light conditions

Examples

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Basic Examples  (3)

Total variation filtering on noisy data:

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Denoise a grayscale image:

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Filter a 3D image:

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Scope  (8)

Options  (4)

Applications  (5)

See Also

WienerFilter  MedianFilter  MeanShiftFilter  PeronaMalikFilter

Introduced in 2010
(8.0)
| Updated in 2012
(9.0)