Survey of deep learning architectures for blind deblurring with PSNR and SSIM benchmarks on GOPRO and Kohler datasets.
Learning to Deblur
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abstract
We describe a learning-based approach to blind image deconvolution. It uses a deep layered architecture, parts of which are borrowed from recent work on neural network learning, and parts of which incorporate computations that are specific to image deconvolution. The system is trained end-to-end on a set of artificially generated training examples, enabling competitive performance in blind deconvolution, both with respect to quality and runtime.
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2019 1verdicts
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Blind Deblurring using Deep Learning: A Survey
Survey of deep learning architectures for blind deblurring with PSNR and SSIM benchmarks on GOPRO and Kohler datasets.