Image compression based on periodic principal components

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

  • Wilmar Hernandez
  • Alfredo Mendez
  • Pablo Alejandro Quezada-Sarmiento
  • Luis Alberto Jumbo-Flores
  • Paolo Mercorelli
  • Vera Tyrsa
  • Patricia Acosta-Vargas
  • Ivan Menes Camejo
  • Jose Rigoberto Muñoz Cagua
  • Willam Bladimir Cevallos Cevallos
In the present paper, the almost periodicity of the first principal components is studied, with the aim of being able to use less information in order to obtain acceptable reconstructions of compressed images. The results of this study show that by working with the periodic principal components of images under analysis, it is possible to obtain an additional reduction to that obtained by using the original principal components. Specifically, it is shown that if the principal components that are considered periodic are replaced by their period plus a trend, it can be said that the reconstruction achieved using these periodic principal components is very close to the reconstruction achieved using the original principal components.
Original languageEnglish
Title of host publicationIECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society
Number of pages8
Place of PublicationPiscataway
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication date01.10.2019
Pages5634-5641
Article number8926747
ISBN (print)978-1-7281-4879-3
ISBN (electronic)978-1-7281-4878-6
DOIs
Publication statusPublished - 01.10.2019
Event45th Annual Conference of the Institute of Electrical and Electronics Engineers' Industrial Electronics Society - 2019 - Lisbon Congress Center, Lisbon, Portugal
Duration: 14.10.201917.10.2019
Conference number: 45
https://iecon2019.org/

Bibliographical note

Funding Information:
This research has been supported by CEDIA-Ecuador (under the research project CEPRA XII-2018-13), Universidad de Las Americas, Quito, Ecuador (under the research project ERa.ERI.WHP.18.01), and Universidad Politecnica de Madrid, Spain.

Publisher Copyright:
© 2019 IEEE.