  We propose a patch-based method for the simultaneous denoising and fusion of
a sequence of RAW multi-exposed images. A spatio-temporal criterion is used to
select similar patches along the sequence, and a weighted principal component
analysis permits to both denoise and fuse the multi exposed data. The overall
strategy permits to denoise and fuse the set of images without the need of
recovering each denoised image in the multi-exposure set, leading to a very
efficient procedure. Several experiments show that the proposed method permits
to obtain state-of-the-art fusion results with real RAW data.
