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Glare is always present in optical acquisition systems, such as photocameras or the eye-bulb. As a consequence, images captured by sensors do not represent an accurate reproduction of the scene, but rather a combination of scene content and glare. We discuss the reasons why this unwanted addition of spread light cannot be removed from an acquired image. To this aim, we cast the problem of glare-removal into an estimation task and focus on the aspects that make the unfolding of glare an ill-posed or ill-conditioned problem—such as nonlinearity, information loss, or eye model uncertainty. For each mechanism of glare formation, we point to the corresponding influence in terms of ill-posedness and ill-conditioning of the problem. We do not aim at proposing or reviewing solutions to the glare problem but rather at identifying more precisely the challenges it poses.
This will count as one of your downloads.
You will have access to both the presentation and article (if available).
High-dynamic range (HDR) imaging is a significant improvement over conventional imaging. After a description of the dynamic range problem in image acquisition, this course focuses on standard methods of creating and manipulating HDR images, replacing myths with measurements of scenes, camera images, and visual appearances. In particular, the course presents measurements about the limits of accurate camera acquisition and the usable range of light for displays of our vision system. Regarding our vision system, the course discusses the role of accurate vs. non-accurate luminance recording for the final appearance of a scene, presenting the quality and the characteristics of visual information actually available on the retina. It ends with a discussion of the principles of tone rendering and the role of spatial comparison.
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