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

Ali Akbar Siddique,Zia Mohy-Ud-Din,M Tahir Qadr

doi:10.1177/0020294020944949

Ali Akbar Siddique, Zia Mohy-Ud-Din + Show 1 more

Open Access

https://doi.org/10.1177/0020294020944949

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Abstract

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.

Highlights

Usage of multimedia information has increased exponentially, due to which there is an enormous amount of data available on Internet and not enough bandwidth to transmit it over the wireless channel; due to these limitations in modern communication medium, a compression process is required to reduce the size of a video for an available bandwidth
An algorithm is proposed that utilizes temporal masking (TM) in Motion vectors (MVs) to reduce bit rate
A video sequence is composed of multiple individual frames, and most of these consecutive frames in a same video sequence will retain a large chunk of information from its predecessor and it will possess temporal activity

Summary

Introduction

Usage of multimedia information has increased exponentially, due to which there is an enormous amount of data available on Internet and not enough bandwidth to transmit it over the wireless channel; due to these limitations in modern communication medium, a compression process is required to reduce the size of a video for an available bandwidth This may lead to certain disturbing artifacts in a coded video stream. Video quality depends on the amount of motion present in a coded stream, every video after compression possessing disturbing artifacts that degrade its quality dramatically.[1] The compression process is classified into two different categories: lossy and lossless Both these algorithms are able to remove unnecessary information to reduce the size of an image or video content.[2] Each person can have a different perception of the distortion depending on the information masked during the process. Motion or temporal masking (TM) can help adjust the relevance-distortion before quantifying its total amount

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