Masking of temporal activity for video quality control, measurement and assessment

Every video stream possesses temporal redundancy based on the amount of motion presenting in it. An ample amount of motion in a video sequence may cause distorting artifacts, and in order to avoid them, there is a possibility to mask the motion or temporal activity that is not noticeable to a human...

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Main Authors: Ali Akbar Siddique, M Tahir Qadr, Zia Mohy-Ud-Din
Format: Article
Language:English
Published: SAGE Publishing 2020-11-01
Series:Measurement + Control
Online Access:https://doi.org/10.1177/0020294020944949
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spelling doaj-016926f672864d40bf8a6aa8be70ef5f2021-02-04T06:05:55ZengSAGE PublishingMeasurement + Control0020-29402020-11-015310.1177/0020294020944949Masking of temporal activity for video quality control, measurement and assessmentAli Akbar Siddique0M Tahir Qadr1Zia Mohy-Ud-Din2Department of Telecommunication Engineering, Sir Syed University of Engineering & Technology, Karachi, PakistanDepartment of Electronics Engineering, Sir Syed University of Engineering & Technology, Karachi, PakistanDepartment of Mechatronics & Biomedical Engineering, Air University, Islamabad, PakistanEvery video stream possesses temporal redundancy based on the amount of motion presenting in it. An ample amount of motion in a video sequence may cause distorting artifacts, and in order to avoid them, there is a possibility to mask the motion or temporal activity that is not noticeable to a human eye in real time. The artifacts such as blockiness and blurriness are instigated in the video sequence as soon as it is subjected to the process of compression, and they tend to become more and more intense with the increase in temporal activity. In this paper, an algorithm is proposed to mask the temporal activity using temporal masking coefficient ( q ) that is unnoticeable by a human eye to bring down the distortion levels. It is possible to adjust the quality of the video sequence by varying the q parameter and thus controlling its overall quality index. Frames are extracted from the video sequence, and displacement or motion vectors are also calculated from the consecutive frames using a bi-directional block matching algorithm. These motion vectors are used to estimate the quantity of motion present between consecutive frames of the same scene. Video sequences used for this purpose are basically H.264 format. Temporal masking is performed on a video sequence with and without the implementation of motion vector. Structural similarity index and peak signal-to-noise ratio are the quality measurement tools used to assess the performance of the proposed algorithm. A bit rate of 1.2% was saved by implementing proposed algorithm at q = 1 in contrast to the standard H.264/Advanced Video Coding.https://doi.org/10.1177/0020294020944949
collection DOAJ
language English
format Article
sources DOAJ
author Ali Akbar Siddique
M Tahir Qadr
Zia Mohy-Ud-Din
spellingShingle Ali Akbar Siddique
M Tahir Qadr
Zia Mohy-Ud-Din
Masking of temporal activity for video quality control, measurement and assessment
Measurement + Control
author_facet Ali Akbar Siddique
M Tahir Qadr
Zia Mohy-Ud-Din
author_sort Ali Akbar Siddique
title Masking of temporal activity for video quality control, measurement and assessment
title_short Masking of temporal activity for video quality control, measurement and assessment
title_full Masking of temporal activity for video quality control, measurement and assessment
title_fullStr Masking of temporal activity for video quality control, measurement and assessment
title_full_unstemmed Masking of temporal activity for video quality control, measurement and assessment
title_sort masking of temporal activity for video quality control, measurement and assessment
publisher SAGE Publishing
series Measurement + Control
issn 0020-2940
publishDate 2020-11-01
description Every video stream possesses temporal redundancy based on the amount of motion presenting in it. An ample amount of motion in a video sequence may cause distorting artifacts, and in order to avoid them, there is a possibility to mask the motion or temporal activity that is not noticeable to a human eye in real time. The artifacts such as blockiness and blurriness are instigated in the video sequence as soon as it is subjected to the process of compression, and they tend to become more and more intense with the increase in temporal activity. In this paper, an algorithm is proposed to mask the temporal activity using temporal masking coefficient ( q ) that is unnoticeable by a human eye to bring down the distortion levels. It is possible to adjust the quality of the video sequence by varying the q parameter and thus controlling its overall quality index. Frames are extracted from the video sequence, and displacement or motion vectors are also calculated from the consecutive frames using a bi-directional block matching algorithm. These motion vectors are used to estimate the quantity of motion present between consecutive frames of the same scene. Video sequences used for this purpose are basically H.264 format. Temporal masking is performed on a video sequence with and without the implementation of motion vector. Structural similarity index and peak signal-to-noise ratio are the quality measurement tools used to assess the performance of the proposed algorithm. A bit rate of 1.2% was saved by implementing proposed algorithm at q = 1 in contrast to the standard H.264/Advanced Video Coding.
url https://doi.org/10.1177/0020294020944949
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