Enhancing image denoising by controlling noise incursion in learned dictionaries
Existing image denoising frameworks via sparse representation using learned dictionaries have an weakness that the dictionary, trained from noisy image, suffers from noise incursion. This paper analyzes this noise incursion, explicitly derives the noise component in the dictionary update step, and p...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/107084 http://hdl.handle.net/10220/25303 http://dx.doi.org/10.1109/LSP.2015.2388712 |