Gradient Vector Flow

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Gradient Vector Flow

The Gradient Vector Flow tool allows calculating the image gradient in a specified direction [1], which is for instance used for active contours algorithms.

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Different algorithms are supported:

GVF: calculates the gradient using the gradient vector flow algorithm;

General GVF: calculates the gradient using a generalized gradient vector flow algorithm;

Differential gradient: calculates the gradient by subtracting values of neighbouring pixels;

Sobel operator: calculates the gradient by convolving filter mask with matrix consisting of image pixels.

During the estimation procedure the following parameters can be set:

Gradient width: distance (in pixels) between two points, the intensity difference which defines the gradient value;

Iterations: number of iterations performed during GVF and GGVF calculation;

Smoothing parameter (μ): regularization parameter governing the trade-off between the first and the second integral term. Smoothing parameters should be set according to the amount of noise present in the image: the higher the noise the bigger the value.

Time step (Δ): is representing the time length for each iteration.

In order to guarantee algorithm convergence, the smoothing parameter and the time step should satisfy the following expression: μ<-1.36*Δt+0.22. Therefore, the Parameters restriction box should be enabled.

By enabling Image Preview and the Show gradient field, the gradient vectors can be visualized.

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Reference

1.Chenyang Xu, Jerry L. Prince. Snakes, Shapes and Gradient Vector Flow, Transactions on Image Processing, March 1998, p. 359-369.