Resize

Scales the input video frames to an arbitrary new resolution, and optionally crops the frame before resizing with sub-pixel precision.

There are trade-offs to be considered between preservation (or augmentation) of image detail and possible artifacts (i.e., oversharpening).

Cropping of the left and top edges respectively, in pixels, before resizing.

As with Crop, these arguments have different functionality, depending on their value:

• If  > zero, these set the width and height of the clip before resizing.
• If <= zero, they set the cropping of the right and bottom edges respectively, before resizing.

Note, there are certain limits:

• clip.Width must be >= (src_left + width)
• clip.Width must be >  (src_left + right)
• clip.Height must be >= (src_top + height)
• clip.Height must be >  (src_top + bottom)

...otherwise it would enlarge ("un-crop") the clip, or reduce width or height to 0, which is not allowed.

• All resizers have an expanded syntax which crops the frame before resizing:

BilinearResize(100, 150, src_left=10, src_top=10, src_width=200, src_height=300)

BilinearResize(100, 150, 10, 10, 200, 300)

Crop(10, 10, 200, 300).BilinearResize(100, 150)

• Note the cropping parameters are all floating point. This allows any Resize filter to be used as a sub-pixel shifter. ^[1]

• Note that Crop gives a hard boundary, whereas the Resize filters interpolate pixels outside the cropped region – depending on the resizer kernel – bilinear, bicubic etc, and not beyond the edge of the image.

• As a general rule,
  • Crop any hard borders or noise; Resize cropping may propagate the noise into the output.
  • Use Resize cropping to maintain accurate edge rendering when excising a part of a complete image.

• Negative cropping is allowed; this results in repeated edge pixels as shown below:

BilinearResize(Width, Height, -64, -64, Width, Height)

BilinearResize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height ] )

BilinearResize uses standard bilinear filtering and is a good choice for smoothing overly sharp sources.

BicubicResize(clip clip, int target_width, int target_height [, float b, float c,
     float src_left, float src_top, float src_width, float src_height ] )

BicubicResize is similar to BilinearResize, except that instead of a linear filtering function it uses the Mitchell-Netravali two-part cubic. The parameters b and c can be used to adjust the properties of the cubic; they are sometimes referred to as "blurring" and "ringing" respectively.

If you are enlarging your video, you will get sharper results with BicubicResize than with BilinearResize. However, if you are shrinking it, you may prefer BilinearResize as it performs some antialiasing.

parameters b and c

float  b, c = 1/3

The default for both b and c is 1/3, which were recommended by Mitchell and Netravali for having the most visually pleasing results.

BlackmanResize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height, int taps ] )

BlackmanResize is a modification of LanczosResize that has better control of ringing artifacts for high numbers of taps.

parameter taps

int  taps = 4

See LanczosResize for an explanation of the taps argument (default 4, range 1-100).

GaussResize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height, float p ] )

GaussResize uses a gaussian resizer, which unlike the bicubics, does not overshoot – but perhaps does not appear as sharp to the eye.

parameter p

float  p = 30.0

Sharpness. Range from about 1 to 100, with 1 being very blurry and 100 being very sharp.

LanczosResize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height, int taps ] )

Lanczos4Resize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height ] )

LanczosResize is a sharper alternative to BicubicResize. It is NOT suited for low bitrate video; the various Bicubic flavours are much better for this.

Lanczos4Resize is a short hand for LanczosResize(taps=4). It produces sharper images than LanczosResize with the default taps=3, especially useful when upsizing a clip.

parameter taps

int  taps = 3

Basically, taps affects sharpness. Default 3, range 1-100. Equal to the number of filter lobes (ignoring mirroring around the origin).

PointResize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height ] )

PointResize is the simplest resizer possible. It uses a Point Sampler or Nearest Neighbour algorithm, which usually results in a very "blocky" image. So in general this filter should only be used, if you intend to have inferior quality, or you need the clear pixel drawings. Useful for magnifying small areas for examination.

Spline16Resize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height ] )

Spline36Resize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height ] )

Spline64Resize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height ] )

Spline16Resize, Spline36Resize and Spline64Resize are three Spline based resizers. They are the (cubic) spline based resizers from Panorama tools that fit a spline through the sample points and then derives the filter kernel from the resulting blending polynomials. See this thread for the technical details.

The rationale for Spline is to be as sharp as possible with less ringing artifacts than LanczosResize produces. Spline16Resize uses √16 or 4 sample points, Spline36Resize uses √36 or 6 sample points, etc ... The more sample points used, the more accurate the resampling. Several resizer comparison pages are given in the External Links section.

• Spline64Resize may be the most accurate of the Resize filters.^Dersch
• Spline16Resize is sharper and rings just a bit (which may be desirable with soft sources),
  and looks pleasing to the eye when enlarging or reducing in moderate amounts.^doom9
• Spline36Resize is somewhere in between the other two.

SincResize(clip clip, int target_width, int target_height [,
     float src_left, float src_top, float src_width, float src_height, int taps ] )

SincResize uses the truncated sinc function. It is very sharp, but prone to ringing artifacts.

parameter taps

int  taps = 4

See LanczosResize for an explanation of the taps argument (default 4, range 1-20).

Crop(10, 10, 200, 300).BilinearResize(100, 150)

which is nearly the same as:

BilinearResize(100, 150, 10, 10, 200, 300)

AviSource("video.avi").BilinearResize(240,180)

AviSource("dv.avi").BilinearResize(352, 240, 8, 0, 704, 480)

which is the same as:

AviSource("dv.avi").BilinearResize(352, 240, 8, 0, -8, -0)

BilinearResize(320, 240, 160, 0, 160, 120)

• AviSynth has completely separate vertical and horizontal resizers. If input is the same as output on one axis, that resizer will be skipped. The resizer with the smallest downscale ratio is called first; this is done to preserve maximum quality, so the second resizer has the best possible picture to work with. Data storing will have an impact on what mods should be used for sizes when resizing and cropping; see Crop restrictions.