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- W3155668052 abstract "We address the problem of non-blind deblurring and demosaicking of noisy raw images. We adapt an existing learning-based approach to RGB image deblurring to handle raw images by introducing a new interpretable module that jointly demosaicks and deblurs them. We train this model on RGB images converted into raw ones following a realistic invertible camera pipeline. We demonstrate the effectiveness of this model over two-stage approaches stacking demosaicking and deblurring modules on quantitive benchmarks. We also apply our approach to remove a camera's inherent blur (its color-dependent point-spread function) from real images, in essence deblurring sharp images." @default.
- W3155668052 created "2021-04-26" @default.
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- W3155668052 date "2021-04-13" @default.
- W3155668052 modified "2023-10-18" @default.
- W3155668052 title "Learning to Jointly Deblur, Demosaick and Denoise Raw Images" @default.
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