Variational approach for the fusion of exposure bracketed pairs
When taking pictures of a dark scene with artificial lighting, ambient light is not sufficient for most cameras to obtain both accurate color and detail information. The exposure bracketing feature usually available in many camera models enables the user to obtain a series of pictures taken in rapid...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universitat Pompeu Fabra |
| Repositorio: | Repositorio Digital de la UPF |
| OAI Identifier: | oai:repositori.upf.edu:10230/41690 |
| Acceso en línea: | http://hdl.handle.net/10230/41690 http://dx.doi.org/10.1109/TIP.2012.2221730 |
| Access Level: | acceso abierto |
| Palabra clave: | Color transfer Image denoising Image fusion Variational methods |
| Sumario: | When taking pictures of a dark scene with artificial lighting, ambient light is not sufficient for most cameras to obtain both accurate color and detail information. The exposure bracketing feature usually available in many camera models enables the user to obtain a series of pictures taken in rapid succession with different exposure times; the implicit idea is that the user picks the best image from this set. But in many cases, none of these images is good enough; in general, good brightness and color information are retained from longer-exposure settings, whereas sharp details are obtained from shorter ones. In this paper, we propose a variational method for automatically combining an exposure-bracketed pair of images within a single picture that reflects the desired properties of each one. We introduce an energy functional consisting of two terms, one measuring the difference in edge information with the short-exposure image and the other measuring the local color difference with a warped version of the long-exposure image. This method is able to handle camera and subject motion as well as noise, and the results compare favorably with the state of the art. |
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