A Parametric Family of Polynomial Wavelets for Signal and Image Processing
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866912837904891904 |
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| author | Cotronei, Mariantonia Themistoclakis, Woula Van Barel, Marc |
| author_facet | Cotronei, Mariantonia Themistoclakis, Woula Van Barel, Marc |
| contents | This paper investigates the potential applications of a parametric family of polynomial wavelets that has been recently introduced starting from de la Vallée Poussin (VP) interpolation at Chebyshev nodes. Unlike classical wavelets, which are constructed on the real line, these VP wavelets are defined on a bounded interval, offering the advantage of handling boundaries naturally while maintaining computational efficiency. In addition, the structure of these wavelets enables the use of fast algorithms for decomposition and reconstruction. Furthermore, the flexibility offered by a free parameter allows a better control of localized singularities, such as edges in images. On the basis of previous theoretical foundations, we show the effectiveness of the VP wavelets for basic signal denoising and image compression, emphasizing their potential for more advanced signal and image processing tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_12403 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Parametric Family of Polynomial Wavelets for Signal and Image Processing Cotronei, Mariantonia Themistoclakis, Woula Van Barel, Marc Numerical Analysis 42C40 (Primary) 65T60, 94A08 (Secondary) This paper investigates the potential applications of a parametric family of polynomial wavelets that has been recently introduced starting from de la Vallée Poussin (VP) interpolation at Chebyshev nodes. Unlike classical wavelets, which are constructed on the real line, these VP wavelets are defined on a bounded interval, offering the advantage of handling boundaries naturally while maintaining computational efficiency. In addition, the structure of these wavelets enables the use of fast algorithms for decomposition and reconstruction. Furthermore, the flexibility offered by a free parameter allows a better control of localized singularities, such as edges in images. On the basis of previous theoretical foundations, we show the effectiveness of the VP wavelets for basic signal denoising and image compression, emphasizing their potential for more advanced signal and image processing tasks. |
| title | A Parametric Family of Polynomial Wavelets for Signal and Image Processing |
| topic | Numerical Analysis 42C40 (Primary) 65T60, 94A08 (Secondary) |
| url | https://arxiv.org/abs/2503.12403 |