Joint Denoising and HDR for RAW Image Sequences

Show simple item record Buades, A. Martorell, O. Sánchez-Beeckman, M. 2024-02-28T07:47:47Z 2024-02-28T07:47:47Z
dc.description.abstract [eng] We propose a patch-based method for the simultaneous denoising and fusion of a sequence of multi-exposed RAW images. A spatio-temporal criterion is used to select similar patches along the sequence, and a weighted principal component analysis (WPCA) simultaneously denoises and fuses the multi-exposed data. The overall strategy permits to denoise and fuse the set of images without the need to recover each denoised image in the multi-exposure set, leading to a very efficient procedure. Moreover, ghosting removal is included naturally as part of the method by {the} way patches are selected and the weighted principal component analysis. Several experiments show that the proposed method obtains state-of-the-art fusion results with real~RAW~data. The method is very flexible, it can be easily adapted to other kinds of noise and extended to video HDR and denoising.
dc.format application/pdf
dc.relation.ispartof Ieee Transactions On Computational Imaging, 2024, vol. 10, p. 277-290
dc.rights , 2024
dc.subject.classification 51 - Matemàtiques
dc.subject.classification 004 - Informàtica
dc.subject.other 51 - Mathematics
dc.subject.other 004 - Computer Science and Technology. Computing. Data processing
dc.title Joint Denoising and HDR for RAW Image Sequences
dc.type info:eu-repo/semantics/article 2024-02-28T07:47:47Z
dc.rights.accessRights info:eu-repo/semantics/openAccess

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