Subjective quality assessment of H.264/AVC encoded low resolution videos

Abstract

Abstract-Advancements in the video processing area have been proliferated by services that require low delay. Such services involve applications being offered at various temporal and spatial resolutions. It necessitates to study the impacts of related video coding conditions upon perceptual quality. But most of studies concerned with quality assessment of videos affected by coding distortions lack in variety of spatio-temporal resolutions. This paper presents a work done on quality assessment of videos encoded by state-of-the-art H.264/AVC standard at different bitrates and frame rates. Overall, 120 test scenarios for video sequences having different spatial and temporal spectral information were studied. The used coded bistreams in this work and the corresponding subjective assessment scores have been made public for the research community to facilitate further studies.

Analysis of the impact of temporal, spatial, and quantization variations on perceptual video quality

“…Subjective experiments conducted using low resolution videos, CIF, in [6] show that frame rate can be compromised to maintain the perceptual quality by keeping the compression ratio at low value. Similar results can be observed in the study reported in reference [7]. Impact of encoding strategy on the quality of MPEG-2 encoded videos, QCIF and CIF, while transmitted over lossy network has been investigated in [8].…”

“…Particularly, the method followed was the single stimulus quality evaluation where a test video sequence is shown once without the presence of any explicit reference, corresponding to the reality where users see only the processed version of the video. Overall, the adopted methodology and lab setup has been summarized in [7]. The subjects who participated in the tests were of both genders, mainly students at the university and some staff members, and all of them were considered to be non-expert in the area of video quality assessment.…”

A No Reference Video Quality Metric Based on Jerkiness Estimation Focusing on Multiple Frame Freezing in Video Streaming

“…The value of bitrate, frame rate, and frame size of a video greatly effects the perceptual quality of a video at any given test condition. There are several studies, such as [25,26], that have been done for conducting the subjective tests under different test conditions.…”

A no-reference machine learning based video quality predictor

“…Particularly, the method followed was single stimulus quality evaluation where a test video sequence is shown once without the presence of any explicit reference, corresponding to the reality where users see only the processed version of videos [15]. A detailed account of these subjective tests is presented in [16]. In order to obtain reliable results out of raw subjective scores, screening of the observers was employed to discard observers that are considered as outliers.…”