| Operators |
shock_filter — Apply a shock filter to an image.
shock_filter(Image : SharpenedImage : Theta, Iterations, Mode, Sigma : )
The operator shock_filter applies a shock filter to the input image Image to sharpen the edges contained in it. The principle of the shock filter is based on the transport of the gray values of the image towards an edge from both sides through dilation and erosion and satisfies the differential equation
The decision between dilation and erosion is made using the sign function s with values {-1,0,+1} on a conventional edge detector. The detector of Canny
To make the edge detection more robust, in particular on noisy images, it can be performed on a smoothed image matrix. This is done by giving the standard deviation of a Gaussian kernel for convolution with the image matrix in the parameter Sigma.
Note that filter operators may return unexpected results if an image with a reduced domain is used as input. Please refer to the chapter Filters.
Input image.
Output image.
Time step.
Default value: 0.5
Suggested values: 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7
Restriction: 0 < Theta <= 0.7
Number of iterations.
Default value: 10
Suggested values: 1, 3, 10, 100
Restriction: Iterations >= 1
Type of edge detector.
Default value: 'canny'
List of values: 'canny', 'laplace'
Smoothing of edge detector.
Default value: 1.0
Suggested values: 0.0, 0.5, 1.0, 2.0, 5.0
Restriction: Theta >= 0
F. Guichard, J. Morel; “A Note on Two Classical Shock Filters and
Their Asymptotics”; Michael Kerckhove (Ed.): Scale-Space and
Morphology in Computer Vision, LNCS 2106, pp. 75-84; Springer, New
York; 2001.
G. Aubert, P. Kornprobst; “Mathematical Problems in Image
Processing”; Applied Mathematical Sciences 147; Springer, New
York; 2002.
Foundation
| Operators |