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Filtering

Filters provide an easy to use, yet powerful tool to remove interfering elements (like noise or ice gradients) from an image. Here, a set of different filters are provided which all apply a filter onto the input stack of images.

A stack of images/3Ds or an individual 3D will be subjected to the selected filter with its respective filter parameters. For more detail on the capabilities of the available filters and their parameters, consult the respective process section below. Since most of the filters just have one input (stack of images) and one output (stack of images w/ applied filter), only divergent in-/outputs are mentioned.

FIXME

Applies a Butterworth Filter with the chosen parameters to the images. A butterworth filter has a smooth transfer function without any discontinuity. The filter functions used in this logic are:

B(Low Pass)= 1/ (1+[D(u,v)/DL ]2n) B(High Pass)= 1- (1/ (1+[D(u,v)/DH]2n))

where D(u,v) is the distance from the origin, n is the order of the filter and DL/DH is the cut frequency.

Parameters Description
Type Select whether you want to apply a highpass or lowpass filter
pass-band Order of the filter n
showFilterFunction Use this option to change the output consisting of complex images showing the filter function instead of the filtered images
stop-band Upper or lower frequency cut-off DL / DH, depending on whether high- or lowpassfilter is selected
Parameters Description
Flip Description of this parameter
Scale factor more description

This processor applies a cosine bandpass, lowpass or highpass filter, respectively, on the images.

Parameters Description
Cosine width [0…1] This value sets the width of the cosine function in the filter mask.
Low frequency [0…1] This value sets the lowpass frequency used for the filtering mask.
High frequency [0…1] This value sets the highpass frequency used for the filtering mask.
showFilterfunction If enabled, the output shows the filter mask according to the set parameters instead of the filtered images.

The DoG is a wavelet mother function of null total sum which approximates the Mexican Hat Wavelet by subtracting a wide from a narrow Gaussian. This filter is applied on each input image and results in feature enhancement through edge detection. Further details can be found here and here . FIXME

Parameters Description
Narrow standard deviation This value sets narrower standard deviation for the DoG method. It describes one of the kernel functions used to perform the filtering procedure. If Narrow standard deviation is larger than Wide standard deviation, the values are swapped.
Wide standard deviation This value sets wider standard deviation for the DoG method. It describes one of the kernel functions used to perform the filtering procedure. If Narrow standard deviation is larger than Wide standard deviation, the values are swapped.
Input Description
FirstInput Input Description 1
SecondInput Input Description 2
ThirdInput Input Description 3: Optional Input in Italic
Output Description
FirstOutput Output Description
New/Changed Header Values Description
headerValue1 what does it say? how is it changed?
headerValue2 what does it say? how is it changed?
headerValue3 what does it say? how is it changed?
headerValue4 what does it say? how is it changed?

Here, a short introduction for the given mode should be placed. Again, state WHAT and WHY this mode us useful in not more than 2 sentences.

Parameters Description
Some changeable parameter Description of this parameter
→ and its sub-parameter more description
Next main parameter and more more more
→ and its sub-parameter … descriptions
Input Description
FirstInput Input Description 1
SecondInput Input Description 2
ThirdInput Input Description 3: Optional Input in Italic
Output Description
FirstOutput Output Description
New/Changed Header Values Description
headerValue1 what does it say? how is it changed?
headerValue2 what does it say? how is it changed?
headerValue3 what does it say? how is it changed?
headerValue4 what does it say? how is it changed?

Here, a short introduction for the given mode should be placed. Again, state WHAT and WHY this mode us useful in not more than 2 sentences.

Parameters Description
Some changeable parameter Description of this parameter
→ and its sub-parameter more description
Next main parameter and more more more
→ and its sub-parameter … descriptions
Input Description
FirstInput Input Description 1
SecondInput Input Description 2
ThirdInput Input Description 3: Optional Input in Italic
Output Description
FirstOutput Output Description
New/Changed Header Values Description
headerValue1 what does it say? how is it changed?
headerValue2 what does it say? how is it changed?
headerValue3 what does it say? how is it changed?
headerValue4 what does it say? how is it changed?

Here, a short introduction for the given mode should be placed. Again, state WHAT and WHY this mode us useful in not more than 2 sentences.

Parameters Description
Some changeable parameter Description of this parameter
→ and its sub-parameter more description
Next main parameter and more more more
→ and its sub-parameter … descriptions
Input Description
FirstInput Input Description 1
SecondInput Input Description 2
ThirdInput Input Description 3: Optional Input in Italic
Output Description
FirstOutput Output Description
New/Changed Header Values Description
headerValue1 what does it say? how is it changed?
headerValue2 what does it say? how is it changed?
headerValue3 what does it say? how is it changed?
headerValue4 what does it say? how is it changed?

Here, a short introduction for the given mode should be placed. Again, state WHAT and WHY this mode us useful in not more than 2 sentences.

Parameters Description
Some changeable parameter Description of this parameter
→ and its sub-parameter more description
Next main parameter and more more more
→ and its sub-parameter … descriptions
Input Description
FirstInput Input Description 1
SecondInput Input Description 2
ThirdInput Input Description 3: Optional Input in Italic
Output Description
FirstOutput Output Description
New/Changed Header Values Description
headerValue1 what does it say? how is it changed?
headerValue2 what does it say? how is it changed?
headerValue3 what does it say? how is it changed?
headerValue4 what does it say? how is it changed?

Here, a short introduction for the given mode should be placed. Again, state WHAT and WHY this mode us useful in not more than 2 sentences.

Parameters Description
Some changeable parameter Description of this parameter
→ and its sub-parameter more description
Next main parameter and more more more
→ and its sub-parameter … descriptions
Input Description
FirstInput Input Description 1
SecondInput Input Description 2
ThirdInput Input Description 3: Optional Input in Italic
Output Description
FirstOutput Output Description
New/Changed Header Values Description
headerValue1 what does it say? how is it changed?
headerValue2 what does it say? how is it changed?
headerValue3 what does it say? how is it changed?
headerValue4 what does it say? how is it changed?

Here, a short introduction for the given mode should be placed. Again, state WHAT and WHY this mode us useful in not more than 2 sentences.

Parameters Description
Some changeable parameter Description of this parameter
→ and its sub-parameter more description
Next main parameter and more more more
→ and its sub-parameter … descriptions
Input Description
FirstInput Input Description 1
SecondInput Input Description 2
ThirdInput Input Description 3: Optional Input in Italic
Output Description
FirstOutput Output Description
New/Changed Header Values Description
headerValue1 what does it say? how is it changed?
headerValue2 what does it say? how is it changed?
headerValue3 what does it say? how is it changed?
headerValue4 what does it say? how is it changed?

In this paragraph, the “HOW a logic works under the hood” and WHY someone should use it can be elaborated with higher detail. Describes a scenario in an image processing workflow where this logic can be used to solve the resulting problem. Also, wikipages, publications or anything else describing the theory behind an algorithm should be linked here, if applicable.