Ghosting free HDR for dynamic scenes via shift-maps

K. Prabhakar, R. Venkatesh Babu
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引用次数: 2

Abstract

Given a set of sequential exposures, High Dynamic Range imaging is a popular method for obtaining high-quality images for fairly static scenes. However, this typically suffers from ghosting artifacts for scenes with significant motion. Also, existing techniques cannot handle heavily saturated regions in the sequence. In this paper, we propose an approach that handles both the issues mentioned above. We achieve robustness to motion (both object and camera) and saturation via an energy minimization formulation with spatio-temporal constraints. The proposed approach leverages information from the neighborhood of heavily saturated regions to correct such regions. The experimental results demonstrate the superiority of our method over state-of-the-art techniques for a variety of challenging dynamic scenes.
通过移位地图为动态场景提供重影免费HDR
给定一组连续曝光,高动态范围成像是获得静态场景高质量图像的流行方法。然而,对于具有显著运动的场景,这通常会受到重影的影响。此外,现有技术无法处理序列中高度饱和的区域。在本文中,我们提出了一种处理上述两个问题的方法。我们通过具有时空约束的能量最小化公式实现对运动(物体和相机)和饱和度的鲁棒性。该方法利用高饱和区域的邻域信息对高饱和区域进行校正。实验结果表明,我们的方法优于最先进的技术,适用于各种具有挑战性的动态场景。
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