Image compression based on periodic principal components
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Authors
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 language | English |
|---|---|
| Title of host publication | IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society |
| Number of pages | 8 |
| Place of Publication | Piscataway |
| Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
| Publication date | 01.10.2019 |
| Pages | 5634-5641 |
| Article number | 8926747 |
| ISBN (Print) | 978-1-7281-4879-3 |
| ISBN (Electronic) | 978-1-7281-4878-6 |
| DOIs | |
| Publication status | Published - 01.10.2019 |
| Event | 45th Annual Conference of the Institute of Electrical and Electronics Engineers' Industrial Electronics Society - 2019 - Lisbon Congress Center, Lisbon, Portugal Duration: 14.10.2019 → 17.10.2019 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.
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