9.54. ITK Min Max Curvature Flow Image Filter

Denoise an image using min/max curvature flow.

Group (Subgroup)

ITKCurvatureFlow (CurvatureFlow)

Description

MinMaxCurvatureFlowImageFilter implements a curvature driven image denoising algorithm. Iso-brightness contours in the grayscale input image are viewed as a level set. The level set is then evolved using a curvature-based speed function:

\f[ I_t = F_{\mbox{minmax}} |\nabla I| \f]

where \f$ F_{\mbox{minmax}} = \max(\kappa,0) \f$ if \f$ \mbox{Avg}{\mbox{stencil}}(x) \f$ is less than or equal to \f$ T{threshold} \f$ and \f$ \min(\kappa,0) \f$ , otherwise. \f$ \kappa \f$ is the mean curvature of the iso-brightness contour at point \f$ x \f$ .

In min/max curvature flow, movement is turned on or off depending on the scale of the noise one wants to remove. Switching depends on the average image value of a region of radius \f$ R \f$ around each point. The choice of \f$ R \f$ , the stencil radius, governs the scale of the noise to be removed.

The threshold value \f$ T_{threshold} \f$ is the average intensity obtained in the direction perpendicular to the gradient at point \f$ x \f$ at the extrema of the local neighborhood.

This filter make use of the multi-threaded finite difference solver hierarchy. Updates are computed using a MinMaxCurvatureFlowFunction object. A zero flux Neumann boundary condition is used when computing derivatives near the data boundary.

Warning

This filter assumes that the input and output types have the same dimensions. This filter also requires that the output image pixels are of a real type. This filter works for any dimensional images, however for dimensions greater than 3D, an expensive brute-force search is used to compute the local threshold.

Reference: “Level Set Methods and Fast Marching Methods”, J.A. Sethian, Cambridge Press, Chapter 16, Second edition, 1999.

See Also

Input Parameter(s)

Parameter Name

Parameter Type

Parameter Notes

Description

Time Step

Scalar Value

Float64

The time step to be used for each iteration.

Number Of Iterations

Scalar Value

UInt32

Specifies the number of iterations (time-step updates) that the solver will perform to produce a solution image

Stencil Radius

Scalar Value

Int32

Set/Get the stencil radius.

Input Cell Data

Parameter Name

Parameter Type

Parameter Notes

Description

Image Geometry

Geometry Selection

Image

Select the Image Geometry Group from the DataStructure.

Input Cell Data

Array Selection

Allowed Types: float32, float64

The image data that will be processed by this filter.

Output Cell Data

Parameter Name

Parameter Type

Parameter Notes

Description

Output Image Data Array

DataObjectName

The result of the processing will be stored in this Data Array.

Example Pipelines

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