Enhancing sparse representation of color images by cross channel transformation

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.

Publication DOI: https://doi.org/10.1371/journal.pone.0279917
Dataset DOI: https://doi.org/10.17036/researchdata.aston.ac.uk.00000590
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied Mathematics & Data Science
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
Additional Information: 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.
Uncontrolled Keywords: Algorithms,Data Compression/methods
Publication ISSN: 1932-6203
Last Modified: 25 Apr 2024 07:20
Date Deposited: 27 Jan 2023 08:50
Full Text Link:
Related URLs: https://journal ... al.pone.0279917 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2023-01
Published Online Date: 2023-01-26
Accepted Date: 2022-12-16
Submitted Date: 2022-09-12
Authors: Rebollo-Neira, Laura (ORCID Profile 0000-0002-7420-8977)
Inacio, Aurelien

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