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Low bit Rate Video Quality Analysis Using NRDPF-VQA Algorithm

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 5 No. 1 (2015)

DOI
10.11591/ijece.v5i1.pp71-77
ISSN
2088-8708, 2088-8708
Published
2015-02-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

In this work, we propose NRDPF-VQA (No Reference Distortion Patch Features Video Quality Assessment) model aims to use to measure the video quality assessment for H.264/AVC (Advanced Video Coding). The proposed method takes advantage of the contrast changes in the video quality by luminance changes. The proposed quality metric was tested by using LIVE video database. The experimental results show that the new index performance compared with the other NR-VQA models that require training on LIVE video databases, CSIQ video database, and VQEG HDTV video database. The values are compared with human score index analysis of DMOS.

Collaboration network of the authors

5 authors · 6 co-authorship links

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  • Narasaraopeta Engineering College
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
D. V. Bhaskar RaoNarasaraopeta Engineering College1
N. Usha RaniAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref 
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Low bit Rate Video Quality Analysis Using NRDPF-VQA Algorithm</dc:title><dc:creator>CH, Subrahmanyam</dc:creator><dc:creator>D, Venkata Rao</dc:creator><dc:creator>N, Usha Rani</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;p&amp;gt;In this work, we propose NRDPF-VQA (No Reference Distortion Patch Features Video Quality Assessment) model aims to use to measure the video quality assessment for H.264/AVC (Advanced Video Coding). The proposed method takes advantage of the contrast changes in the video quality by luminance changes. The proposed quality metric was tested by using LIVE video database. The experimental results show that the new index performance compared with the other NR-VQA models that require training on LIVE video databases, CSIQ video database, and VQEG HDTV video database. The values are compared with human score index analysis of DMOS.&amp;lt;/p&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2015-02-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v5i1.pp71-77</dc:identifier><dc:identifier>10.11591/ijece.v5i1.pp71-77</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 5 No 1 (2015); 71</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/5618/4779</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>