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Updated: May 18, 2026
06:25
Stereoacuity Improvement using Random-Dot Video Games
Published on: January 14, 2020
Video quality pooling adaptive to perceptual distortion severity
Jincheol Park1, Kalpana Seshadrinathan, Sanghoon Lee
1Wireless Network Laboratory, Department of Electrical and Electronics Engineering, Yonsei University, Seoul 120-749, Korea. dewofdawn@yonsei.ac.kr
Summary
Transient video distortions significantly impact perceived quality. This study introduces a content-adaptive pooling strategy to better assess video quality by emphasizing worst scores and motion effects.
Area of Science:
- Digital video processing
- Perceptual video quality assessment
Background:
- Severe transient spatial and/or temporal video distortions greatly affect perceived video quality.
- Existing video quality assessment (VQA) algorithms require improved methods to account for these distortions.
Purpose of the Study:
- To investigate the distribution of spatio-temporally local quality scores from VQA algorithms on distorted videos.
- To propose a novel content-adaptive spatial and temporal pooling strategy for enhanced video quality assessment.
Main Methods:
- Analyzing quality score distributions from multiple VQA algorithms on compressed and lossy transmitted videos.
- Developing a pooling strategy that adaptively emphasizes "worst" spatial and temporal scores.
- Incorporating the perceptual impact of large-area cohesive motion, such as egomotion.
Main Results:
- The proposed content-adaptive pooling strategy effectively enhances video quality assessment.
- Demonstrated efficacy across three different VQA algorithms.
- Validated on established video quality databases (LIVE and EPFL-PoliMI).
Conclusions:
- The developed pooling strategy offers a more accurate method for assessing video quality, particularly in the presence of transient distortions.
- This approach improves the robustness of VQA algorithms by considering content adaptivity and perceptual motion effects.
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