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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer International Publishing
2022
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| Online Access: | https://hdl.handle.net/1721.1/137554.2 |