Butteraugli

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Abstract
Author Asd-g
Version v2.0.1
Download Butteraugli
Category Debug filter
License GPLv3
Discussion

Contents

[edit] Description

Butteraugli estimating filter for the psychovisual similarity of two images.

A quality metric for lossy image and video compression.

This is a port of the VapourSynth plugin butteraugli.

libjxl's Butteraugli is used.

[edit] Requirements


[edit] Syntax and Parameters

Butteraugli (clip reference, clip distorted, bool "distmap", float "intensity_target", bool "linput")


reference   =
distorted   =
Clips that are use for estimating the psychovisual similarity. They must be in planar RGB format (8-32bit).


bool  distmap = false
Whether to return heatmap instead of distorted clip


float  intensity_target = 80.0
Viewing conditions screen nits


bool  linput = false
True: The input clips must have linear transfer functions.
False: The input clips are assumed in sRGB color space and internal conversion to linear transfer function is done.


The psychovisual similarity of the clips will be stored as frame property '_FrameButteraugli' in the output clip. Larger values indicate to bigger difference.


[edit] Examples

# Return the difference between the clips with displayed all frame properties alongside with '_FrameButteraugli'
Butteraugli(clip1, clip2, distmap=true, linput=false)
propShow()


# Return clip2 with displayed the value of the frame property '_FrameButteraugli'.
Butteraugli(clip1, clip2, linput=false)
ScriptClip("""Subtitle(String(propGetFloat("_FrameButteraugli")))""")


[edit] Changelog

Version      Date            Changes
v2.0.1 2022/12/04 - Changed to be slightly more sensitive to low freq (DC) errors.
v2.0.0 2021/10/20 - Updated to butteraugli library from libjxl.
v1.1.0 2020/11/06 - Added support for 10..32-bit clips. - Added parameters 'hf_asymmetry' and 'linput'.
v1.0.2 2020/11/02 - Registered as MT_MULTI_INSTANCE. - Used faster butteraugli lib.
v1.0.0 2020/10/31 - Initial release


[edit] External Links

  • GitHub - Source code repository.




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