Overview of State-of-the-Art Algorithms for Stack-Based High-Dynamic Range (HDR) Imaging

P. Sen
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引用次数: 6

Abstract

Modern digital cameras have very limited dynamic range, which makes them unable to capture the full range of illumination in natural scenes. Since this prevents them from accurately photographing visible detail, researchers have spent the last two decades developing algorithms for high-dynamic range (HDR) imaging which can capture a wider range of illumination and therefore allow us to reconstruct richer images of natural scenes. The most practical of these methods are stack-based approaches which take a set of images at different exposure levels and then merge them together to form the final HDR result. However, these algorithms produce ghost-like artifacts when the scene has motion or the camera is not perfectly static. In this paper, we present an overview of state-of-the-art deghosting algorithms for stackbased HDR imaging and discuss some of the tradeoffs of each.
基于堆栈的高动态范围(HDR)成像的最新算法概述
现代数码相机的动态范围非常有限,这使得它们无法捕捉到自然场景中的全范围照明。由于这阻碍了他们准确地拍摄可见细节,研究人员花了过去二十年的时间开发高动态范围(HDR)成像算法,可以捕捉更大范围的照明,从而使我们能够重建更丰富的自然场景图像。这些方法中最实用的是基于堆栈的方法,它采用一组不同曝光水平的图像,然后将它们合并在一起形成最终的HDR结果。然而,当场景有运动或相机不是完全静止时,这些算法会产生幽灵般的伪影。在本文中,我们概述了基于堆栈的HDR成像的最先进的去重影算法,并讨论了每种算法的一些权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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