Network Working Group T. Daede
Internet-Draft J. Moffitt
Intended status: Informational Mozilla
Expires: September 10, 2015 March 09, 2015
Video Codec Testing and Quality Measurement
draft-daede-netvc-testing-00
Abstract
This document describes guidelines and procedures for evaluating an
internet video codec specified at the IETF. This covers subjective
and objective tests, test conditions, and materials used for the
test.
Status of This Memo
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This Internet-Draft will expire on September 10, 2015.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Subjective Metrics . . . . . . . . . . . . . . . . . . . . . 2
3. Objective Metrics . . . . . . . . . . . . . . . . . . . . . . 2
3.1. PSNR . . . . . . . . . . . . . . . . . . . . . . . . . . 3
3.2. PSNR-HVS-M . . . . . . . . . . . . . . . . . . . . . . . 3
3.3. SSIM . . . . . . . . . . . . . . . . . . . . . . . . . . 3
3.4. Fast Multi-Scale SSIM . . . . . . . . . . . . . . . . . . 4
4. Comparing and Interpreting Results . . . . . . . . . . . . . 4
4.1. Graphing . . . . . . . . . . . . . . . . . . . . . . . . 4
4.2. Bjontegaard . . . . . . . . . . . . . . . . . . . . . . . 4
5. Test Sequences . . . . . . . . . . . . . . . . . . . . . . . 4
5.1. Sources . . . . . . . . . . . . . . . . . . . . . . . . . 4
5.2. Usage Scenarios . . . . . . . . . . . . . . . . . . . . . 5
6. Automation . . . . . . . . . . . . . . . . . . . . . . . . . 6
7. Informative References . . . . . . . . . . . . . . . . . . . 6
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 7
1. Introduction
When developing an internet video codec, changes and additions to the
codec need to be decided based on their performance tradeoffs. In
addition, measurements are needed to determine when the codec has met
its performance goals. This document specifies how the tests are to
be carried about to ensure valid comparisons and good decisions.
2. Subjective Metrics
Subjective testing is the preferable method of testing video codecs.
Because the IETF does not have testing resources of its own, it has
to rely on the resources of its participants. For this reason, even
if the group agrees that a particular test is important, if no one
volunteers to do it, or if volunteers do not complete it in a timely
fashion, then that test should be discarded. This ensures that only
important tests be done in particular, the tests that are important
to participants.
3. Objective Metrics
Objective metrics are used in place of subjective metrics for easy
and repeatable experiments. Most objective metrics have been
designed to correlate with subjective scores.
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The following descriptions give an overview of the operation of each
of the metrics. Because implementation details can sometimes vary,
the exact implementation is specified in C in the Daala tools
repository [DAALA-GIT].
All of the metrics described in this document are to be applied to
the luma plane only. In addition, they are single frame metrics.
When applied to the video, the scores of each frame are averaged to
create the final score.
Codecs are allowed to internally use downsampling, but must include a
normative upsampler, so that the metrics run at the same resolution
as the source video. In addition, some metrics, such as PSNR and
FASTSSIM, have poor behavior on downsampled images, so it must be
noted in test results if downsampling is in effect.
3.1. PSNR
PSNR is a traditional signal quality metric, measured in decibels.
It is directly drived from mean square error (MSE), or its square
root (RMSE). The formula used is:
20 * log10 ( MAX / RMSE )
or, equivalently:
10 * log10 ( MAX^2 / MSE )
which is the method used in the dump_psnr.c reference implementation.
3.2. PSNR-HVS-M
The PSNR-HVS metric performs a DCT transform of 8x8 blocks of the
image, weights the coefficients, and then calculates the PSNR of
those coefficients. Several different sets of weights have been
considered. [PSNRHVS] The weights used by the dump_pnsrhvs.c tool in
the Daala repository have been found to be the best match to real MOS
scores.
3.3. SSIM
SSIM (Structural Similarity Image Metric) is a still image quality
metric introduced in 2004 [SSIM]. It computes a score for each
individual pixel, using a window of neighboring pixels. These scores
can then be averaged to produce a global score for the entire image.
The original paper produces scores ranging between 0 and 1.
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For the metric to appear more linear on BD-rate curves, the score is
converted into a nonlinear decibel scale:
-10 * log10 (1 - SSIM)
3.4. Fast Multi-Scale SSIM
Multi-Scale SSIM is SSIM extended to multiple window sizes [MSSSIM].
This is implemented in the Fast implementation by downscaling the
image a number of times, and computing SSIM over the same number of
pixels, then averaging the SSIM scores together [FASTSSIM]. The
final score is converted to decibels in the same manner as SSIM.
4. Comparing and Interpreting Results
4.1. Graphing
When displayed on a graph, bitrate is shown on the X axis, and the
quality metric is on the Y axis. For clarity, the X axis bitrate is
always graphed in the log domain. The Y axis metric should also be
chosen so that the graph is approximately linear. For metrics such
as PSNR and PSNR-HVS, the metric result is already in the log domain
and is left as-is. SSIM and FASTSSIM, on the other hand, return a
result between 0 and 1. To create more linear graphs, this result is
converted to a value in decibels:
-1 * log10 ( 1 - SSIM )
4.2. Bjontegaard
The Bjontegaard rate difference, also known as BD-rate, allows the
comparison of two different codecs based on a metric. This is
commonly done by fitting a curve to each set of data points on the
plot of bitrate versus metric score, and then computing the
difference in area between each of the curves. A cubic polynomial
fit is common, but will be overconstrained with more than four
samples. For higher accuracy, at least 10 samples and a linear
piecewise fit should be used.
5. Test Sequences
5.1. Sources
Lossless test clips are preferred for most tests, because the
structure of compression artifacts in already-compressed clips may
introduce extra noise in the test results. However, a large amount
of content on the internet needs to be recompressed at least once, so
some sources of this nature are useful. The encoder should run at
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the same bit depth as the original source. In addition, metrics need
to support operation at high bit depth. If one or more codecs in a
comparison do not support high bit depth, sources need to be
converted once before entering the encoder.
The JCT-VC standards organization includes a set of standard test
clips for video codec testing, and parameters to run the clips with
[L1100]. These clips are not publicly available, but are very useful
for comparing to published results.
Xiph publishes a variety of test clips collected from various
sources.
The Blender Open Movie projects provide a large test base of lossless
cinematic test material. The lossless sources are available, hosted
on Xiph.
5.2. Usage Scenarios
Sources are divided into several categories to test different
scenarios the codec will be required to operate in. Example sources
are listed for each scenario.
o Still images are useful when comparing intra coding performance.
Xiph.org has four sets of lossless, one megapixel images that have
been converted into YUV 4:2:0 format.
* subset1 (50 images)
* subset2 (50 images)
* subset3 (1000 images)
* subset4 (1000 images)
o Streaming video consists of cinematic content, with a minimum
source resolution of 1920x1080 at 24 to 30 frames per second.
* Sintel
* Tears of Steel
* Kimono1
* Tennis
* PeopleOnStreet
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o Videoconferencing content is high framerate, and varying HD
resolutions.
* KristenAndSara
* FourPeople
* Johnny
o Screensharing content is low framerate, high resolution content
typical of a computer desktop.
* SlideEditing
* SlideShow
o Game streaming content is synthetically generated content, with
varying resolutions but typically recorded at 60 frames per
second.
* ChinaSpeed
* Touhou
6. Automation
Frequent objective comparisons are extremely beneficial while
developing a new codec. Several tools exist in order to automate the
process of objective comparisons. The Compare-Codecs tool allows BD-
rate curves to be generated for a wide variety of codecs
[COMPARECODECS]. The Daala source repository contains a set of
scripts that can be used to automate the various metrics used. In
addition, these scripts can be run automatically utilizing
distributed computer for fast results [AWCY].
7. Informative References
[AWCY] Xiph.Org, "Are We Compressed Yet?", 2015, <https://
arewecompressedyet.com/>.
[COMPARECODECS]
Alvestrand, H., "Compare Codecs", 2015,
<http://compare-codecs.appspot.com/>.
[DAALA-GIT]
Xiph.Org, "Daala Git Repository", 2015,
<http://git.xiph.org/?p=daala.git;a=summary>.
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[FASTSSIM]
Chen, M. and A. Bovik, "Fast structural similarity index
algorithm", 2010, <http://live.ece.utexas.edu/publications
/2011/chen_rtip_2011.pdf>.
[L1100] Bossen, F., "Common test conditions and software reference
configurations", JCTVC L1100, 2013,
<http://phenix.int-evry.fr/jct/>.
[MSSSIM] Wang, Z., Simoncelli, E., and A. Bovik, "Multi-Scale
Structural Similarity for Image Quality Assessment", n.d.,
<http://www.cns.nyu.edu/~zwang/files/papers/msssim.pdf>.
[PSNRHVS] Egiazarian, K., Astola, J., Ponomarenko, N., Lukin, V.,
Battisti, F., and M. Carli, "A New Full-Reference Quality
Metrics Based on HVS", 2002.
[SSIM] Wang, Z., Bovik, A., Sheikh, H., and E. Simoncelli, "Image
Quality Assessment: From Error Visibility to Structural
Similarity", 2004,
<http://www.cns.nyu.edu/pub/eero/wang03-reprint.pdf>.
Authors' Addresses
Thomas Daede
Mozilla
Email: tdaede@mozilla.com
Jack Moffitt
Mozilla
Email: jack@metajack.im
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