Burst Image Deblurring Using Permutation Invariant Convolutional Neural Networks
© Springer Nature Switzerland AG 2018. We propose a neural approach for fusing an arbitrary-length burst of photographs suffering from severe camera shake and noise into a sharp and noise-free image. Our novel convolutional architecture has a simultaneous view of all frames in the burst, and by cons...
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Format: | Article |
Language: | English |
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Springer International Publishing
2021
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Online Access: | https://hdl.handle.net/1721.1/137554 |