Difference between revisions of "PanoTools Anti Aliasing Filters"

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! Name
 
! Name
 
! f(x)
 
! f(x)
! Kernel size
+
! Kernel size<br>(radius)
 +
! Comment
 
|-
 
|-
| aabox || 8 || Box Filter || [[Image:plot_s_filter_8.png]] || 0.5  
+
| aabox || 8 || Box Filter || [[Image:plot_s_filter_8.png]] || 0.5 || sometimes called ''nearest neighbor''
 
|-
 
|-
| aatriangle || 9 || Bartlett/Triangle Filter || [[Image:plot_s_filter_9.png]] || 1.0  
+
| aatriangle || 9 || Bartlett/Triangle Filter || [[Image:plot_s_filter_9.png]] || 1.0 || sometimes called ''bilinear''
 
|-
 
|-
 
| aahermite || 10 || Hermite Filter || [[Image:plot_s_filter_10.png]] || 1.0  
 
| aahermite || 10 || Hermite Filter || [[Image:plot_s_filter_10.png]] || 1.0  
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| aaquadratic || 16 || Quadardic Filter || [[Image:plot_s_filter_16.png]] || 1.5  
 
| aaquadratic || 16 || Quadardic Filter || [[Image:plot_s_filter_16.png]] || 1.5  
 
|-
 
|-
| aacubic || 17 || Cubic Filter || [[Image:plot_s_filter_17.png]] || 2.0  
+
| aacubic || 17 || Cubic Filter || [[Image:plot_s_filter_17.png]] || 2.0 || default filter in [[Photoshop]]
 
|-
 
|-
 
| aacatrom || 18 || Catmull-Rom Filter || [[Image:plot_s_filter_18.png]] || 2.0  
 
| aacatrom || 18 || Catmull-Rom Filter || [[Image:plot_s_filter_18.png]] || 2.0  

Revision as of 13:40, 12 November 2007

Since version 2.7.10 the PanoTools library contains several interpolation filter that avoid aliasing. Those filters use a dynamic kernel size where the size of the filter kernel is calculated for each pixel.

There are two theoretical types of kernels that have an equal right for existence. Kernels based on the Gaussian distribution and kernels based on the Sinc function. Both kernels have an infinite width so a windowing function is used to limit the kernel size for practical reasons. Gaussian based kernels do not contain negative values, sinc based do.

The values in the plot describe the contribution of a pixel depending on the distance from the center. A wider kernel in the center means a more blurry image but if it is to narrow it tends to produce aliasing. If the kernel contains negative values the images also gets sharpened. Some examples: If you look at the plots you can see that a Hamming Filter produces blurrier image then the Blackmann Filter. The Lanczos2 Filter introduces more sharpening then the Mitchell Filter because of the larger negative areas.

short ID Name f(x) Kernel size
(radius)
Comment
aabox 8 Box Filter Plot s filter 8.png 0.5 sometimes called nearest neighbor
aatriangle 9 Bartlett/Triangle Filter Plot s filter 9.png 1.0 sometimes called bilinear
aahermite 10 Hermite Filter Plot s filter 10.png 1.0
aahanning 11 Hanning Filter Plot s filter 11.png 1.0
aahamming 12 Hamming Filter Plot s filter 12.png 1.0
aablackman 13 Blackmann Filter Plot s filter 13.png 1.0
aagaussian 14 Gaussian 1/sqrt(2) Filter (blury) Plot s filter 14.png 1.25
aagaussian2 15 Gaussian 1/2 Filter (sharper) Plot s filter 15.png 1.0
aaquadratic 16 Quadardic Filter Plot s filter 16.png 1.5
aacubic 17 Cubic Filter Plot s filter 17.png 2.0 default filter in Photoshop
aacatrom 18 Catmull-Rom Filter Plot s filter 18.png 2.0
aamitchell 19 Mitchell Filter Plot s filter 19.png 2.0
aalanczos2 20 Lanczos2 Filter Plot s filter 20.png 2.0
aalanczos3 21 Lanczos3 Filter Plot s filter 21.png 3.0
aablackmanbessel 22 Blackman/Bessel Filter Plot s filter 22.png 3.2383
aablackmansinc 23 Blackman/sinc Filter Plot s filter 23.png 4.0

Some examples.