A Kalman-Filtering Approach to High Dynamic Range Imaging for Measurement Applications
A Kalman-Filtering Approach to High Dynamic Range Imaging for Measurement Applications
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DOI：
10.1109/tip.2011.2164414
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发表时间：
2012-02
影响因子：
10.6
通讯作者：
Eric Dedrick;D. Lau
中科院分区：
文献类型：
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作者：
Eric Dedrick;D. Lau
计算摄影中的高动态范围成像（HDRI）方法解决场景的动态范围超过图像传感器在单次曝光中可以捕获的动态范围的情况。HDRI技术也已被用于构建辐射图在测量应用中，不幸的是，在这些应用中使用的HDRI算法的设计和评估很少受到关注。在本文中，我们开发了一种新的HDRI技术的基础上逐像素卡尔曼滤波和评估其性能使用客观指标，本文也介绍。在所提出的实验中，这种新技术实现了高达9.4 dB的信噪比改善，并可以实现高达29%的改进，在辐射精度比经典的方法。
High dynamic range imaging (HDRI) methods in computational photography address situations where the dynamic range of a scene exceeds what can be captured by an image sensor in a single exposure. HDRI techniques have also been used to construct radiance maps in measurement applications; unfortunately, the design and evaluation of HDRI algorithms for use in these applications have received little attention. In this paper, we develop a novel HDRI technique based on pixel-by-pixel Kalman filtering and evaluate its performance using objective metrics that this paper also introduces. In the presented experiments, this new technique achieves as much as 9.4-dB improvement in signal-to-noise ratio and can achieve as much as a 29% improvement in radiometric accuracy over a classic method.