Jack Tumblin
Abstract
High contrast images are common in night scenes and other scenes that include dark shadows and bright light sources. These scenes are difficult to display because their contrasts greatly exceed the range of most display devices for images. As a result, the image constrasts are compressed or truncated, obscuring subtle textures and details. Humans view and understand high contrast scenes easily, “adapting” their visual response to avoid compression or truncation with no apparent loss of detail. By imitating some of these visual adaptation processes, we developed methods for the improved display of high-contrast images. The first builds a display image from several layers of lighting and surface properties. Only the lighting layers are compressed, drastically reducing contrast while preserving much of the image detail. This method is practical only for synthetic images where the layers can be retained from the rendering process. The second method interactively adjusts the displayed image to preserve local contrasts in a small “foveal” neighborhood. Unlike the first method, this technique is usable on any image and includes a new tone reproduction operator. Both methods use a sigmoid function for contrast compression. This function has no effect when applied to small signals but compresses large signals to fit within an asymptotic limit. We demonstrate the effectiveness of these approaches by comparing processed and unprocessed images.
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Index Terms
- Two methods for display of high contrast images
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Reviews
Shawn Neely
The authors describe two contrasting methods (pun intended) for the display of images having a high dynamic range in brightness. The ratio of light intensity is formalized into a measure of contrast, and the authors address the problem of displaying high-contrast images on typical display devices such as CRT monitors. Much of the motivation comes from the amazing adaptive capabilities of the human visual system, which can easily adapt to huge ranges of brightness, even within a single scene. The paper covers previous research in this area, as well as some traditional techniques used by artists and photographers to capture the detail in a scene, both in the shadows and in the highlights. The first method described in depth involves decomposition of the scene into various lighting layers, such as glossy reflections, and is suitable for computer graphics rendering where this kind of layered information is available. The second method considered interactively adjusts portions of the displayed image in a local area corresponding to the point of interest directed at the fovea. The authors used a mouse cursor to indicate such a region of interest in the displayed image, but an automatic eye-tracking device could certainly be applied. Overall, the paper is well written but is intended for an expert audience. Readers should be familiar with some of the extensive references. The first method described could be applied to any static computer-generated image, viewed using video, film, or print media. The second method requires an interactive mechanism for use at a computer workstation. The results will likely be of interest to those who have previously considered the problem of how best to display images with both bright and dark detail.
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