Video codec comparison using the dynamic optimizer framework

Ioannis Katsavounidis; Liwei Guo

doi:10.1117/12.2322118

17 September 2018 Video codec comparison using the dynamic optimizer framework

Ioannis Katsavounidis, Liwei Guo

Proceedings Volume 10752, Applications of Digital Image Processing XLI; 107520Q (2018) https://doi.org/10.1117/12.2322118
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

We present a new methodology that allows for more objective comparison of video codecs, using the recently published Dynamic Optimizer framework. We show how this methodology is relevant primarily to non-real time encoding for adaptive streaming applications and can be applied to any existing and future video codecs. By using VMAF, Netflix’s open-source perceptual video quality metric, in the dynamic optimizer, we offer the possibility to do visual perceptual optimization of any video codec and thus produce optimal results in terms of PSNR and VMAF. We focus our testing using full-length titles from the Netflix catalog. We include results from practical encoder implementations of AVC, HEVC and VP9. Our results show the advantages and disadvantages of different encoders for different bitrate/quality ranges and for a variety of content.

Conference Presentation

Citation Download Citation

Ioannis Katsavounidis and Liwei Guo "Video codec comparison using the dynamic optimizer framework", Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107520Q (17 September 2018); https://doi.org/10.1117/12.2322118

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available