High dynamic range imaging: problems of video exposure bracketing, luminance calibration and gloss editing
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Two-dimensional, conventional images are gradually losing their hegemony, leaving room for novel formats. Among these, 8 bit images give place to high dynamic range (HDR) image formats, allowing to improve colour gamut and visibility of details in dark and bright areas leading to a more immersive viewing experience. It opens wide opportunities for post-processing, which can be useful for artistic rendering, enhancement of viewing experience or medical applications. Simultaneously, light-field scene representation as well is gaining importance, propelled by the recent reappearance of virtual reality, the improvement of both acquisition techniques, and computational and storage capabilities. Light-field data as well allows to achieve a broad range of effects in post-production: among others, it enables a change of a camera position, an aperture or a focal length. It facilitates object insertions and simplifies visual effects workflow by integrating 3D nature of visual effects with 3D nature of light fields. Content generation is one of the stumbling blocks in these realms. Sensor limitations of a conventional camera do not allow to capture wide dynamic range. This especially is the case for mobile devices, where small sensors are optimised for capturing in high-resolution. The "HDR mode" often encountered on such devices, relies on techniques called "exposure fusion" and allows to partially overcome the limited range of a sensor. The HDR video at the same time remains a challenging problem. We suggest a solution for an HDR video capturing on a mobile device. We analyse dynamic range of motion regions, the regions which are the most prone to reconstruction artefacts, and suggest a real-time exposure selection algorithm. Further, an HDR content visualization task often requires an input to be in absolute values. We address this problem by presenting a calibration algorithm that can be applied to existent imagery and does not require any additional measurement hardware. Finally, as light fields use becomes more common, a key challenge is the ability to edit or modify the appearance of the objects in the light field. To this end, we propose a multidimensional filtering approach in which the specular highlights are filtered in the spatial and angular domains to target a desired increase of the material roughness.