TECHNIQUES FOR LIMITING THE INFLUENCE OF IMAGE ENHANCEMENT OPERATIONS ON PERCEPTUAL VIDEO QUALITY ESTIMATIONS

Patent №

US 11,202,103

Granted

2021-12-14

Filed 2021

Owner

NETFLIX, INC.

Lab

AI components

4

ml · vision · planning · evo

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17157871

In various embodiments, a tunable VMAF application reduces an amount of influence that image enhancement operations have on perceptual video quality estimates. In operation, the tunable VMAF application computes a first value for a first visual quality metric based on reconstructed video content and a first enhancement gain limit. The tunable VMAF application computes a second value for a second visual quality metric based on the reconstructed video content and a second enhancement gain limit. Subsequently, the tunable VMAF application generates a feature value vector based on the first value for the first visual quality metric and the second value for the second visual quality metric. The tunable VMAF application executes a VMAF model based on the feature value vector to generate a tuned VMAF score that accounts, at least in part, for at least one image enhancement operation used to generate the reconstructed video content.

AI classification

Planning1.00
Machine learning1.00
Vision1.00
Evolutionary computation0.96
AI hardware0.18
Knowledge representation0.01
Natural language0.00
Speech0.00

Ownership

NETFLIX, INC.

assignment · 583350531

Assignors

LI, ZHI

On an employer assignment, the assignors are typically the inventors.

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