Burst deblurring: Removing camera shake through fourier burst accumulation

Published

Conference Paper

© 2015 IEEE. Numerous recent approaches attempt to remove image blur due to camera shake, either with one or multiple input images, by explicitly solving an inverse and inherently ill-posed deconvolution problem. If the photographer takes a burst of images, a modality available in virtually all modern digital cameras, we show that it is possible to combine them to get a clean sharp version. This is done without explicitly solving any blur estimation and subsequent inverse problem. The proposed algorithm is strikingly simple: it performs a weighted average in the Fourier domain, with weights depending on the Fourier spectrum magnitude. The method's rationale is that camera shake has a random nature and therefore each image in the burst is generally blurred differently. Experiments with real camera data show that the proposed Fourier Burst Accumulation algorithm achieves state-of-the-art results an order of magnitude faster, with simplicity for on-board implementation on camera phones.

Full Text

Duke Authors

Cited Authors

  • Delbracio, M; Sapiro, G

Published Date

  • October 14, 2015

Published In

Volume / Issue

  • 07-12-June-2015 /

Start / End Page

  • 2385 - 2393

International Standard Serial Number (ISSN)

  • 1063-6919

International Standard Book Number 13 (ISBN-13)

  • 9781467369640

Digital Object Identifier (DOI)

  • 10.1109/CVPR.2015.7298852

Citation Source

  • Scopus