IPedge
Synopsis
enhance edges in an ip_Image
Input Ports
|
&in_image |
ip_Image |
|
&in_roi |
ip_Roi |
Parameters
|
MethodsRB |
UIradioBox |
select the edge detection technique |
|
Filter Width |
slider |
set width of convolution kernels |
|
Filter Height |
slider |
set height of convolution kernels |
Output Ports
|
dst |
ip_Image_Out |
|
TmpField |
IPfld |
|
obj |
output renderable object |
Description
IPedge performs an edge enhancement operation using the algorithm specified.
The algorithms use convolution kernels to sharpen an image in the horizontal direction and then in the vertical direction. The algorithms then perform a quadratic add on the resulting images. Images are converted to floating point before performing the convolutions.
Input Ports
-
&in_image
-
The input is a reference to an ip_Image.
&in_roi
-
ip_Roi. An optional region of interest. The data must be of type byte.
Parameters
-
MethodsRB
-
UIradioBox. Selects which edge detection technique to perform. The choices are:
•
Prewiit
-
Roberts
-
Compass
-
Frei Chan
-
Marr Hildreth (variable kernel)
-
Nevatia Babu
-
Robinson 3
-
Robinson 5
-
Macleod (variable kernel)
-
Argyle (variable kernel)
-
Kirsh
-
Boxcar
-
Sobel
-
Derivative of Gaussian (variable kernel)
-
Weighted Line
-
Unweighted Line
-
Filter Width
Filter Height -
float sliders. Some of the algorithms, such as the Argyle, Macleod, Marr Hildreth, and the Derivative of Gaussian use variable width kernels. Filter Width and Filter Height set the width and height of these variable width kernels. The sliders only appear for the selected method as appropriate.
The default for both is 3.0. Their range is 0.1 to 10.0.
The variables specify the functional size of the kernel, not the actual size. A particular algorithm generates the actual kernel size from these values. A variable width kernel is useful because you can make the width smaller to detect smaller detail, or larger to ignore noisy edges in an image.
Be aware that you can supply widths that will produce large kernels, which will require large amounts of processing time. In these cases, you may find that you can perform an edge enhancement operation faster if you first perform a fourier transform on the image.
Output Ports
-
dst
-
The output is a new ip_Image of the same type and number of bands as the input ip_Image.
-
TmpField
-
This output is the ip_Image converted back into an AVS/Express field.
-
obj
-
This is a renderable version of the output.
Example
Libraries.Examples.Image_Processing.IPedge
File
v/ip.v
See also
Not applicable.
