# Difference between revisions of "PanoTools Anti Aliasing Filters"

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− | {{Glossary|Since version 2.7.10 the [[PanoTools]] library contains several [[interpolation]] | + | {{Glossary|Since version 2.7.10 the [[PanoTools]] library contains several [[interpolation]] filters that avoid [[aliasing]].|1}} Those filters use a dynamic kernel size where the size of the filter kernel is calculated for each pixel. The kernel size in the table refers to the kernel used if there is no resizing (f.e. rotation only). If image size is reduced a larger kernel is needed which increases execution times. |

− | There are two | + | There are two types of kernels with equal right to exist. Non-sharpening kernels (ID 8 to 17) based on the [[wikipedia:Normal distribution|Gaussian distribution]] and sharpening kernels (ID 18 to 23) based on the [[wikipedia:Sinc function|Sinc function]]. Both kernel types 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 | + | 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 too 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. |

{| class="wikitable" | {| class="wikitable" |

## Latest revision as of 21:10, 1 November 2008

Since version 2.7.10 the PanoTools library contains several interpolation filters that avoid aliasing. Those filters use a dynamic kernel size where the size of the filter kernel is calculated for each pixel. The kernel size in the table refers to the kernel used if there is no resizing (f.e. rotation only). If image size is reduced a larger kernel is needed which increases execution times.

There are two types of kernels with equal right to exist. Non-sharpening kernels (ID 8 to 17) based on the Gaussian distribution and sharpening kernels (ID 18 to 23) based on the Sinc function. Both kernel types 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 too 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 | 0.5 | sometimes called nearest neighbor
| |

aatriangle | 9 | Bartlett/Triangle Filter | 1.0 | sometimes called bilinear
| |

aahermite | 10 | Hermite Filter | 1.0 | ||

aahanning | 11 | Hanning Filter | 1.0 | ||

aahamming | 12 | Hamming Filter | 1.0 | ||

aablackman | 13 | Blackmann Filter | 1.0 | ||

aagaussian | 14 | Gaussian 1/sqrt(2) Filter (blury) | 1.25 | ||

aagaussian2 | 15 | Gaussian 1/2 Filter (sharper) | 1.0 | ||

aaquadratic | 16 | Quadratic Filter | 1.5 | ||

aacubic | 17 | Cubic Filter | 2.0 | default filter in Photoshop | |

aacatrom | 18 | Catmull-Rom Filter | 2.0 | ||

aamitchell | 19 | Mitchell Filter | 2.0 | ||

aalanczos2 | 20 | Lanczos2 Filter | 2.0 | ||

aalanczos3 | 21 | Lanczos3 Filter | 3.0 | ||

aablackmanbessel | 22 | Blackman/Bessel Filter | 3.2383 | ||

aablackmansinc | 23 | Blackman/sinc Filter | 4.0 |

Some examples.