Edges
Gradient Max
This method performs a gradient filtering. Based on the sum of a 2 x 2 matrix in the X-and Y-direction, a gradient image is calculated and using the larger of the two components. The edges are darker than that of the method Gradient Sum.
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Parameter |
Description |
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|---|---|---|
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Normalization |
Defines how out-of-range pixel values are mapped. The calculated pixel values of the output image may be out-of-range and are mapped into the available range. |
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- |
Clip |
Values exceeding the pixel value range are set to the highest value available (white), values falling short of the pixel value range are set to the lowest value available (black). The effect corresponds to underexposure or overexposure. This means that in some cases information is lost.
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- |
Automatic |
Normalizes the pixel values automatically to the available pixel value range. The highest resulting value is mapped to the maximum pixel value, the lowest resulting value to 0. As a result, the whole range of resulting pixel values is compressed evenly.
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Gradient Sum
This method performs a gradient filtering. Based on the sum of a 2 x 2 matrix in the X-and Y-direction, a gradient image is calculated. The edges are brighter than that of the method Gradient Max.
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Parameter |
Description |
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|---|---|---|
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Normalization |
Defines how out-of-range pixel values are mapped. The calculated pixel values of the output image may be out-of-range and are mapped into the available range. |
|
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- |
Clip |
Values exceeding the pixel value range are set to the highest value available (white), values falling short of the pixel value range are set to the lowest value available (black). The effect corresponds to underexposure or overexposure. This means that in some cases information is lost.
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- |
Automatic |
Normalizes the pixel values automatically to the available pixel value range. The highest resulting value is mapped to the maximum pixel value, the lowest resulting value to 0. As a result, the whole range of resulting pixel values is compressed evenly.
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Highpass
This method performs high-pass filtering. The high pass filter is defined as the difference between the original image and the low-pass filtered original.
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Parameter |
Description |
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|---|---|---|
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Normalization |
Defines how out-of-range pixel values are mapped. The calculated pixel values of the output image may be out-of-range and are mapped into the available range. |
|
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- |
Clip |
Values exceeding the pixel value range are set to the highest value available (white), values falling short of the pixel value range are set to the lowest value available (black). The effect corresponds to underexposure or overexposure. This means that in some cases information is lost.
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- |
Automatic |
Normalizes the pixel values automatically to the available pixel value range. The highest resulting value is mapped to the maximum pixel value, the lowest resulting value to 0. As a result, the whole range of resulting pixel values is compressed evenly.
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- |
Wrap |
If a resulting value is larger than the maximum pixel value of the image, the difference exceeding the maximum pixel value is added to 0. Similarly, if a resulting value is below 0, the resulting pixel value is the maximum pixel value minus the difference falling below 0.
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- |
Shift |
Normalizes the output to the value "pixel value + maximum pixel value/2". As a result, all resulting values are mapped to the available value range. The middle value of the pixel value range remains constant. Values left and right of the middle value are changed progressively, so that values inside the pixel value range are changed only slightly. Values outside the pixel value range are changed strongly and mapped to the fringes of the pixel value range.
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- |
Absolute |
Converts negative pixel values into positive values. Positive pixel values exceeding the maximum pixel value are set to the maximum pixel value.
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Parameter |
Description |
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|---|---|---|
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Count |
Here you set the number of repetitions. I.e. the number of times the function is applied sequentially to the respective result of the filtering. The effect is increased correspondingly. |
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Kernel Size |
You can set the filter size in the x-, y- and z-direction, symmetrically around the subject pixel. This should be the size of the transition region between objects and background match. |
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Laplace
This function performs a Laplace highpass filter on an image.
The calculation is based on a 3 x 3 x 3 Laplace operator in all directions. The function does not show smooth gray value changes very well.
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Parameter |
Description |
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|---|---|---|
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Normalization |
Defines how out-of-range pixel values are mapped. The calculated pixel values of the output image may be out-of-range and are mapped into the available range. |
|
|
- |
Clip |
Values exceeding the pixel value range are set to the highest value available (white), values falling short of the pixel value range are set to the lowest value available (black). The effect corresponds to underexposure or overexposure. This means that in some cases information is lost.
|
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- |
Automatic |
Normalizes the pixel values automatically to the available pixel value range. The highest resulting value is mapped to the maximum pixel value, the lowest resulting value to 0. As a result, the whole range of resulting pixel values is compressed evenly.
|
|
- |
Wrap |
If a resulting value is larger than the maximum pixel value of the image, the difference exceeding the maximum pixel value is added to 0. Similarly, if a resulting value is below 0, the resulting pixel value is the maximum pixel value minus the difference falling below 0.
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- |
Shift |
Normalizes the output to the value "pixel value + maximum pixel value/2". As a result, all resulting values are mapped to the available value range. The middle value of the pixel value range remains constant. Values left and right of the middle value are changed progressively, so that values inside the pixel value range are changed only slightly. Values outside the pixel value range are changed strongly and mapped to the fringes of the pixel value range.
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- |
Absolute |
Converts negative pixel values into positive values. Positive pixel values exceeding the maximum pixel value are set to the maximum pixel value.
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Local Variance
This method is an edge filter, which calculates the variance of each pixel with its neighboring pixels by the lateral filter size. The variance is calculated in the x and y directions and each pixel in the output image represents the average of the two variances.
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Parameter |
Description |
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|---|---|---|
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Kernel Size |
Specifies the number of pixels in the different directions taken into account to calculate the variance. |
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Normalization |
Defines how out-of-range pixel values are mapped. The calculated pixel values of the output image may be out-of-range and are mapped into the available range. |
|
|
- |
Clip |
Values exceeding the pixel value range are set to the highest value available (white), values falling short of the pixel value range are set to the lowest value available (black). The effect corresponds to underexposure or overexposure. This means that in some cases information is lost.
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- |
Automatic |
Normalizes the pixel values automatically to the available pixel value range. The highest resulting value is mapped to the maximum pixel value, the lowest resulting value to 0. As a result, the whole range of resulting pixel values is compressed evenly.
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Roberts
This method calculates a gradient image using the Roberts filter matrix. Large gray value differences between neighbors are shown as light gray values. No changes are indicated by a value of 0 (black). Edges are thinner than with the Sobel method.
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Parameter |
Description |
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|---|---|---|
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Normalization |
Defines how out-of-range pixel values are mapped. The calculated pixel values of the output image may be out-of-range and are mapped into the available range. |
|
|
- |
Clip |
Values exceeding the pixel value range are set to the highest value available (white), values falling short of the pixel value range are set to the lowest value available (black). The effect corresponds to underexposure or overexposure. This means that in some cases information is lost.
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- |
Automatic |
Normalizes the pixel values automatically to the available pixel value range. The highest resulting value is mapped to the maximum pixel value, the lowest resulting value to 0. As a result, the whole range of resulting pixel values is compressed evenly.
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Sobel
Sobel calculates a gradient image using a Sobel filter.
This method indicates gray value changes in the image. Large differences between neighbors are displayed as bright gray values, no changes are indicated by a value of 0 (zero). The pixels in the output image are calculated with the Sobel differential operator on the basis of a 3 x 3 x 3 fold of the input image.
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Parameter |
Description |
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|---|---|---|
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Normalization |
Defines how out-of-range pixel values are mapped. The calculated pixel values of the output image may be out-of-range and are mapped into the available range. |
|
|
- |
Clip |
Values exceeding the pixel value range are set to the highest value available (white), values falling short of the pixel value range are set to the lowest value available (black). The effect corresponds to underexposure or overexposure. This means that in some cases information is lost.
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- |
Wrap |
If a resulting value is larger than the maximum pixel value of the image, the difference exceeding the maximum pixel value is added to 0. Similarly, if a resulting value is below 0, the resulting pixel value is the maximum pixel value minus the difference falling below 0.
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- |
Shift |
Normalizes the output to the value "pixel value + maximum pixel value/2". As a result, all resulting values are mapped to the available value range. The middle value of the pixel value range remains constant. Values left and right of the middle value are changed progressively, so that values inside the pixel value range are changed only slightly. Values outside the pixel value range are changed strongly and mapped to the fringes of the pixel value range.
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- |
Automatic |
Normalizes the pixel values automatically to the available pixel value range. The highest resulting value is mapped to the maximum pixel value, the lowest resulting value to 0. As a result, the whole range of resulting pixel values is compressed evenly.
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