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Sharing pictures has become a very popular practice among consumers. Most recent cameras, displays, and smartphones can capture and display images in high dynamic range and wide colour gamut, contributing to an increase of this type of content. It is a well-known fact that pictures contain information that could cause various security and privacy issues. This is in particular true because high dynamic range pictures exhibit more information when compared to conventional images resulting in an increased invasion of privacy. Lack of proper solutions to overcome privacy can hinder a wide spread adoption of high dynamic range pictures shared in social networks. For example, dark areas of a content that are otherwise difficult to view in a conventional picture become more visible. It is therefore natural that mechanisms are offered to protect privacy while sharing pictures also in high dynamic range. In this paper, we propose an architecture to share high dynamic range images captured by high-end smartphones while offering a mechanism to protect privacy. In our approach, the high dynamic range picture is tone-mapped into a lower dynamic range version which reduces its degree of invasiveness as far as privacy is concerned. Eventually, any remaining privacy sensitive areas in the picture can be further protected (blurring of faces, masking cars licence plates, etc.). The core of the proposed architecture conforms to both JPEG XT, a recently standardised format that offers backward compatibility with legacy JPEG and to JPEG Systems under development. The proposed solution allows to publicly share a protected version of the high dynamic range image tone-mapped to a standard dynamic range picture. The latter can go through transmorphing operation to further protect it. Authorised users can access the original high dynamic range picture. The architecture as described above has been implemented as an app for smartphones running Android OS. We demonstrate feasibility and usefulness of this approach and discuss its advantages when compared to conventional image sharing such as those used in social networks.
SPIE2020
