Institute for Telecommunication Sciences / Research / Quality of Experience / Video Quality Research / Reduced Reference Metrics / Reduced Reference Metrics
Reduced Reference (RR) Video Quality Metrics
2025, A Quick History of ITS Research on RR Metrics
This white paper provides an overview of ITS research on reduced reference (RR) metrics from 1989 to 2011.
Circa 1996, Motivation for Digital Video Quality Metrics
This white paper from the late '90s explains the need for new video quality metrics, as video delivery changed from analog to digital.
1996, Insights into Video Quality Metrics from Early ITS Research
This set of white papers describes the ITS video quality metric research from 1989 to 1996. The algorithms described in these white papers were submitted to ATIS for the T1A1 validation test, 1993 to 1994. These ideas matured into the VQM software released between 2000 to 2005. For more information on the T1A1 validation effort, including videos and subject ratings, see the video quality project data.
Circa 2010, Detecting Large Edges with the Spatial Information (SI) Filter
This white paper describes a spatial information (SI) filter developed by NTIA/ITS. MATLAB® code is provided. The SI filter detects long edges and estimates edge angle.
Circa 2010, Description of Video Quality Metric (VQM) Software
This white paper describes the RR video quality metrics released by ITS between 2000 to 2010. The white paper gives an overview of the VQM Software tools in the VQM software GitHub repository.
Circa 2008, Proof-of-concept RR Metric Software Overview
The vision behind RR video quality metrics was to enable real-time video quality assessment by deploying two probes: one extract features from the source video and another to extract features from the impaired video. These low bandwidth features would be collected at a single location for analysis.
This line of research culminated in the Command Line Video Quality Metric (CVQM) software. This white paper provides a written guide that describes how to use the CVQM software, and the VQM software repository provides code. CVQM demonstrates how to logically split the ITS metrics into an RR implementation. The other code in the VQM repository was developed for research purposes, so both video streams must be available to a single computer. This white paper is the only manual for the CVM software.
The CVQM software code provides the best code for people who want to understand, use, or port the ITS RR metrics. The code was cleaned up significantly, when compared to the batch processing software (in sub-folder bvqm) and the library of code we used internally for our research (in sub-folder its_video).
2012, Video Quality Metrics Tutorial
By Margaret Pinson, 2012
This 2012 Video Quality Metrics Tutorial uses Microsoft PowerPoint® 2010 slides with audio. Start the slideshow to hear the audio. Subtitles are provided in the notes section for each page. Microsoft provides support on ways to view a PowerPoint presentation for Windows® on their website.
This tutorial provides an overview of the RR video quality metrics and other algorithms available in the VQM software, including guidance on which calibration options and models suit different purposes. Other topics covered are the different types of models, mapping multiple subjective datasets onto a single scale, objective video quality model validation, and the Consumer Digital Video Library.
RR Metric Publications
Most of the video quality projects' publications from 1989 to 2011 focus on RR metric development. The list identifies key publications that describe final algorithms and completed lines of research.
- Margaret H. Pinson and Stephen Wolf, “A New Standardized Method for Objectively Measuring Video Quality,” Journal Article, September 2004
- Stephen Wolf and Margaret H. Pinson, “Video Quality Measurement Techniques,” Technical Report NTIA TR-02-392, June 2002
- Margaret H. Pinson and Stephen Wolf, “Low Bandwidth Reduced Reference Video Quality Monitoring System,” Conference Paper, January 2005
- Margaret H. Pinson and Stephen Wolf, “Video scaling estimation technique,” Technical Memorandum NTIA TM-05-417, January 2005
- Margaret H. Pinson and Stephen Wolf, “Reduced Reference Video Calibration Algorithms,” Technical Report NTIA TR-08-433b, November 2007
- Stephen Wolf, “A No Reference (NR) and Reduced Reference (RR) Metric for Detecting Dropped Video Frames,” Technical Memorandum NTIA TM-09-456, October 2008
- Stephen Wolf, “A No Reference (NR) and Reduced Reference (RR) Metric for Detecting Dropped Video Frames,” Conference Paper, January 2009
- Stephen Wolf and Margaret H. Pinson, “Reference Algorithm for Computing Peak Signal to Noise Ratio (PSNR) of a Video Sequence with a Constant Delay,” Technical Contribution, February 2009
- Stephen Wolf, “A Full Reference (FR) Method Using Causality Processing for Estimating Variable Video Delays,” Technical Memorandum NTIA TM-10-463, October 2009