The Little Engine That Could: Regularization by Denoising (RED)
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Abstract
Removal of noise from an image is an extensively studied problem in image processing. Indeed, the recent advent of sophisticated and highly effective denoising algorithms has led some to believe that existing methods are touching the ceiling in terms of noise removal performance. Can we leverage this impressive achievement to treat other tasks in image processing? Recent work has answered this question positively, in the form of the Plug-and-Play Prior ($P^3$) method, showing that any inverse problem can be handled by sequentially applying image denoising steps. This relies heavily on the ADMM optimization technique in order to obtain this chained denoising interpretation. Is this the only way in which tasks…
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Topics
Keywords
- Deblurring
- Noise reduction
- Regularization (linguistics)
- Inverse problem
- Computer science
- Image processing
- Mathematical optimization
- Leverage (statistics)
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