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A Denoising Algorithm for CT Image Using Low-rank Sparse Coding
We propose a denoising method of CT image based on low-rank sparse coding. The proposed method constructs an adaptive dictionary of image patches and estimates the sparse coding regularization parameters using the Bayesian interpretation. A low-rank approximation approach is used to simultaneously c...
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| Publicat a: | Proc SPIE Int Soc Opt Eng |
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| Autors principals: | , , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2018
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6759222/ https://ncbi.nlm.nih.gov/pubmed/31551644 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/12.2292890 |
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