A significant research outcome from the IP4EC ERC Starting Grant has been to propose a vision model for contrast perception that can be realized as an image-dependent non-linear transformation that can accurately reproduce the detail and contrast directly visible in a scene. The model is based on findings from psychophysical and neurophysiological studies and is well suited to the statistics of natural images. The resulting transform is automatic (no need for user-selected parameters) and of extremely low computational complexity, making it a good candidate for real-time applications. It produces images and videos that look natural, without any halos, spurious colors or artifacts. The model has been validated through psychophysical tests that confirm that it outperforms other state of the art algorithms in terms of users’ preference. A European patent application has been filed.The core idea for this Proof of Concept proposal is to take this research outcome, our vision model, and make a series of products that highlight its capabilities on three distinct scenarios: image and video capture, professional post-production of photography and cinema, and rendering in computer graphics. Specifically, this project will produce, in a B2C commercial approach, a free web application and commercial mobile apps for iOS and Android systems intended for the general public, plus commercial software for professionals in three media industries: a Nuke plug-in for cinema post-production, a Photoshop plug-in for photographers, and a Unity plug-in for videogame development. We will formulate a business plan around these products, that also show the potential of our model for other applications like on-chip implementation on camera, on-set monitorization for cinema shoots, format conversion in HDR TV broadcast, or image enhancement for virtual reality headsets, for which we intend to license our technology and provide services, in a B2B commercial approach.