Abstract
Transformations for enhancing sparsity in the approximation of color images by 2D atomic decomposition are discussed. The sparsity is firstly considered with respect to the most significant coefficients in the wavelet decomposition of the color image. The discrete cosine transform is singled out as an effective 3 point transformation for this purpose. The enhanced feature is further exploited by approximating the transformed arrays using an effective greedy strategy with a separable highly redundant dictionary. The relevance of the achieved sparsity is illustrated by a simple encoding procedure. On typical test images the compression at high quality recovery is shown to significantly improve upon JPEG and WebP formats.
Original language | English |
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Article number | e0279917 |
Pages (from-to) | e0279917 |
Number of pages | 17 |
Journal | PLoS ONE |
Volume | 18 |
Issue number | 1 |
Early online date | 26 Jan 2023 |
DOIs | |
Publication status | Published - Jan 2023 |
Bibliographical note
Copyright: © 2023 Rebollo-Neira, Inacio. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Keywords
- Algorithms
- Data Compression/methods
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Data underpinning article: 'Enhancing sparse representation of color images by cross channel transformation'
Rebollo-Neira, L. (Creator) & Inacio, A. (Creator), Aston Data Explorer, 4 Jan 2023
DOI: 10.17036/researchdata.aston.ac.uk.00000590, https://researchdata.aston.ac.uk/id/eprint/590/
Dataset