Joint demosaicking and denoising consists in reconstructing a color image from the noisy raw data output by the sensor of a digital camera. We adopt a variational formulation in which the reconstructed image has minimal total variation under the constraint of consistency with the available measurements. This way, the recovered color image has smooth chrominance but the sharp edges are maintained and the noise is transferred to the luminance channel. This channel is denoised subsequently.
With the adoption of pervasive surveillance systems and the development of efficient automatic face matchers, the question of preserving privacy becomes paramount. In this context, automated face de-identification is revived. Typical solutions based on eyes masking or pixelization, while commonly used in news broadcasts, produce very unnatural images. More sophisticated solutions were sparingly introduced in the literature, but they fail to account for fundamental constraints such as the visual likeliness of de-identified images. In contrast, we identify essential principles and build upon efficient techniques to derive an automated face de-identification solution meeting our predefined criteria. More specifically, our approach relies on a set of face donors from which it can borrow various face components (eyes, chin, etc.). Faces are then de-identified by substituting their own face components with the donors' ones, in such a way that an automatic face matcher is fooled while the appearance of the generated faces are as close as possible to original faces. Experiments on several datasets validate the approach and show its ability both in terms of privacy preservation and visual quality.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.