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RAW Image Files: The Way To HDR Images From A Single Exposure

机译:RAW图像文件:一次曝光即可获得HDR图像的方法

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摘要

HDR image formation and display has been an argument of extreme interest even when digital cameras were not yet consumer products. While recent research in both fields has seen very interesting works, none is really revolutionary, since what goes on behind the scene has been left basically unchanged. In the image formation field in particular, a lot of energy has been spent so to solve the problems that arise when taking multiple exposures: illumination change, camera shake and in-scene movement. In this paper we approach HDR image formation from a different perspective, which tries to solve in one move all the mentioned problems. More specifically, we propose a method that is able to estimate missing exposures for HDR image formation starting from only one under-exposed shot. Estimation is done through artificial neural networks: the development of a mathematical model is a highly desirable, but time consuming task. The results are are very interesting, although not perfect, and suggest that further research might lead to a suitable solution.
机译:即使数码相机还不是消费类产品,HDR图像的形成和显示也引起了人们极大的兴趣。尽管最近在这两个领域的研究都看到了非常有趣的作品,但没有一个是真正的革命性作品,因为幕后发生的事情基本上没有改变。特别是在图像形成领域,已花费大量精力来解决在进行多次曝光时出现的问题:照明变化,相机抖动和场景移动。在本文中,我们从不同的角度研究了HDR图像的形成,试图一口气解决所有上述问题。更具体地说,我们提出一种方法,该方法能够仅从一个曝光不足的镜头开始估算HDR图像形成的缺失曝光。估计是通过人工神经网络完成的:数学模型的开发是一项非常理想的工作,但是非常耗时。结果虽然不完美,但非常有趣,表明进一步的研究可能会找到合适的解决方案。

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