Performance Evaluation of AVC and HEVC for E-Learning:  Optimizing Quality and Reducing Bandwidth Usage

Oğuz Kırat; Tarık Yerlikaya; Emir Öztürk

Article Details

Performance Evaluation of AVC and HEVC for E-Learning: Optimizing Quality and Reducing Bandwidth Usage

Authors:

Oğuz Kırat | Tarık Yerlikaya | Emir Öztürk

Publisher:

Dicle University

Main Topics:

Resim ve Video Kodlama | Video İşleme

Journal:

Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi Vol.14 Issue 4, pp.581-591

Document Type:

Article

Publication Date:

12/2023

Document Language:

English

Document ID (Org No.):

2001307368

pISSN:

1309-8640

Keywords:

Abstract:

 E-learning has experienced a surge in popularity, particularly during and after the COVID-19 pandemic. Online learning has proven to be a vital tool for students and educators to continue academic activities while adhering to social distancing guidelines and during the times of natural disasters that disrupt the conventional learning environments. It also offers accessibility to disabled students and those facing challenges to reach to the traditional learning. But due to increased demand, it is crucial to optimize cost of transmission while minimizing bandwidth usage while maintaining high-quality video transmission. To optimize cost and reduce network load, it is essential to minimize bandwidth usage while maintaining high-quality video. In response to this need, we present a novel dataset consisting of four e-learning scenarios. We encoded this dataset using various resolutions, bit rates, and encoder presets, and evaluated it in terms of encoding time, and quality using full-reference objective quality metrics such as MSE, PSNR, and SSIM. After experimenting with more than 1400 videos and configurations of encoders and codecs, we found out that it is possible to transmit videos in exceptional quality at bitrates as low as 5 Mbps for e-learning scenarios. We also present detailed results about correlation between file size, quality and encoding time to make optimizations for specific bandwidth, target quality or encoding speed.

 E-learning has experienced a surge in popularity, particularly during and after the COVID-19 pandemic. Online learning has proven to be a vital tool for students and educators to continue academic activities while adhering to social distancing guidelines and during the times of natural disasters that disrupt the conventional learning environments. It also offers accessibility to disabled students and those facing challenges to reach to the traditional learning. But due to increased demand, it is crucial to optimize cost of transmission while minimizing bandwidth usage while maintaining high-quality video transmission. To optimize cost and reduce network load, it is essential to minimize bandwidth usage while maintaining high-quality video. In response to this need, we present a novel dataset consisting of four e-learning scenarios. We encoded this dataset using various resolutions, bit rates, and encoder presets, and evaluated it in terms of encoding time, and quality using full-reference objective quality metrics such as MSE, PSNR, and SSIM. After experimenting with more than 1400 videos and configurations of encoders and codecs, we found out that it is possible to transmit videos in exceptional quality at bitrates as low as 5 Mbps for e-learning scenarios. We also present detailed results about correlation between file size, quality and encoding time to make optimizations for specific bandwidth, target quality or encoding speed.

 E-learning has experienced a surge in popularity, particularly during and after the COVID-19 pandemic. Online learning has proven to be a vital tool for students and educators to continue academic activities while adhering to social distancing guidelines and during the times of natural disasters that disrupt the conventional learning environments. It also offers accessibility to disabled students and those facing challenges to reach to the traditional learning. But due to increased demand, it is crucial to optimize cost of transmission while minimizing bandwidth usage while maintaining high-quality video transmission. To optimize cost and reduce network load, it is essential to minimize bandwidth usage while maintaining high-quality video. In response to this need, we present a novel dataset consisting of four e-learning scenarios. We encoded this dataset using various resolutions, bit rates, and encoder presets, and evaluated it in terms of encoding time, and quality using full-reference objective quality metrics such as MSE, PSNR, and SSIM. After experimenting with more than 1400 videos and configurations of encoders and codecs, we found out that it is possible to transmit videos in exceptional quality at bitrates as low as 5 Mbps for e-learning scenarios. We also present detailed results about correlation between file size, quality and encoding time to make optimizations for specific bandwidth, target quality or encoding speed.

 E-learning has experienced a surge in popularity, particularly during and after the COVID-19 pandemic. Online learning has proven to be a vital tool for students and educators to continue academic activities while adhering to social distancing guidelines and during the times of natural disasters that disrupt the conventional learning environments. It also offers accessibility to disabled students and those facing challenges to reach to the traditional learning. But due to increased demand, it is crucial to optimize cost of transmission while minimizing bandwidth usage while maintaining high-quality video transmission. To optimize cost and reduce network load, it is essential to minimize bandwidth usage while maintaining high-quality video. In response to this need, we present a novel dataset consisting of four e-learning scenarios. We encoded this dataset using various resolutions, bit rates, and encoder presets, and evaluated it in terms of encoding time, and quality using full-reference objective quality metrics such as MSE, PSNR, and SSIM. After experimenting with more than 1400 videos and configurations of encoders and codecs, we found out that it is possible to transmit videos in exceptional quality at bitrates as low as 5 Mbps for e-learning scenarios. We also present detailed results about correlation between file size, quality and encoding time to make optimizations for specific bandwidth, target quality or encoding speed.

Article Details

Performance Evaluation of AVC and HEVC for E-Learning: Optimizing Quality and Reducing Bandwidth Usage

Authors:

Oğuz Kırat | Tarık Yerlikaya | Emir Öztürk

Publisher:

Dicle University

Main Topics:

Resim ve Video Kodlama | Video İşleme

Journal:

Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi Vol.14 Issue 4, pp.581-591

Document Type:

Article

Publication Date:

12/2023

Document Language:

English

Document ID (Org No.):

2001307368

pISSN:

1309-8640

AVC

Compression

E-Learning

HEVC

Video Encoding

Video Quality AssessmentAVC

Compression

E-Learning

HEVC

Video Encoding

Video Quality Assessment

Issues

Article Details

Authors: Oğuz Kırat | Tarık Yerlikaya | Emir Öztürk

Publisher: Dicle University

Main Topics: Resim ve Video Kodlama | Video İşleme

Journal: Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi Vol.14 Issue 4, pp.581-591

Document Type: Article

Publication Date: 12/2023

Document Language: English

Document ID (Org No.): 2001307368

pISSN: 1309-8640

Issues

Authors:

Oğuz Kırat | Tarık Yerlikaya | Emir Öztürk

Publisher:

Dicle University

Main Topics:

Resim ve Video Kodlama | Video İşleme

Journal:

Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi Vol.14 Issue 4, pp.581-591

Document Type:

Article

Publication Date:

12/2023

Document Language:

English

Document ID (Org No.):

2001307368

pISSN:

1309-8640