Eyeon:Manual/Tool Reference/Transform/Resize

From VFXPedia

< Eyeon:Manual | Tool Reference | Transform
Revision as of 09:25, 17 April 2008 by Daniel (Talk | contribs)
(diff) ← Older revision | Current revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Resize [Rsz]

Image:Icon_Resize.png

Use the Resize tool to increase or decrease the resolution of an input image. This is useful for converting images from one format to another (for example, from film to video resolution).

Contents


Controls Tab

Width

This controls the new resolution for the image along the X axis.

Height

This controls the new resolution for the image along the Y axis.

Keep Aspect

When toggled on, the Resize tool maintains the aspect of the original image, preserving the original ratio between width and height.

Reset Size

Reset the image dimensions to the original size of the image.

Reset Size

Reset the image dimensions to the original size of the image.

Only Use Filter in HiQ

The Resizetool will normally use the fast Nearest Neighbor filter for any non-HiQ renders, where speed is more important than full accuracy. Disable this checkbox to force Resize to always use the selected filter for all renders.

Change Pixel Aspect

Enable this checkbox to reveal a Pixel Aspect control that can be used to change the pixel aspect that the image is considered to have. See the Frame Formats chapter for details on how pixel aspect operates in Fusion.

Filter Method

When rescaling a pixel, surrounding pixels are often used to give a more realistic result. There are various algorithms for combining these pixels, called filters. More complex filters can give better results, but are usually slower to calculate. The best filter for the job will often depend on the amount of scaling and on the contents of the image itself.

Nearest Neighbor
This skips or duplicates pixels as needed. This produces the fastest but crudest results.
Box
This is a simple interpolation resize of the image.
Linear
This uses a simplistic filter, which produces relatively clean and fast results.
Quadratic
This filter produces a nominal result. It offers a good compromise between speed and quality.
Cubic
This produces better results with continuous tone images but is slower than Quadratic. If the images have fine detail in them, the results may be blurrier than desired.
Catmull-Rom
This produces good results with continuous tone images which are resized down. Produces sharp results with finely detailed images.
Gaussian
This is very similar in speed and quality to Quadratic.
Mitchell
This is similar to Catmull-Rom but produces better results with finely detailed images. It is slower than Catmull-Rom.
Lanczos
This is very similar to Mitchell and Catmull-Rom but is a little cleaner and also slower.
Sinc
This is an advanced filter that produces very sharp, detailed results, however, it may produce visible `ringing' in some situations.
Bessel
This is similar to the Sinc filter but may be slightly faster.
Window Method

Some filters, such as Sinc and Bessel, require an infinite number of pixels to calculate exactly. To speed up this operation, a windowing function is used to approximate the filter and limit the number of pixels required. This control appears when a filter that requires windowing is selected.

Hanning
This is a simple tapered window.
Hamming
Hamming is a slightly tweaked version of Hanning.
Blackman
A window with a more sharply tapered falloff.
Kaiser
A more complex window, with results between Hamming and Blackman.
Note

Most of the Resize tool's filters are useful only when making an image larger. When shrinking images, it is common to use the Linear filter, however, the Catmull-Rom filter will apply some sharpening to the results and may be useful for preserving detail when scaling down an image.

Because this tool changes the physical resolution of the image, we do not normally advise animating the controls.



The contents of this page are copyright by eyeon Software.



Tips for Resize (edit)

For those who would like to learn more about the maths behind the various filters, Turkowski (1990) (PDF) is a good place to start.