Rank-Based Radiometric Calibration
Rank-Based Radiometric Calibration
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DOI：
10.2352/j.imagingsci.technol.2018.62.5.050404
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发表时间：
2018-09
期刊：
影响因子：
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通讯作者：
H. Gong;G. Finlayson;Maryam M. Darrodi;Robert B. Fisher
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文献类型：
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作者：
H. Gong;G. Finlayson;Maryam M. Darrodi;Robert B. Fisher
对于机器视觉算法和专业摄影师来说，原始图像比JPEG图像更有用，因为原始图像保留了像素值和从场景测量的光线之间的线性关系。如果存在可以预测如何将原始图像映射到相应的渲染图像(例如JPEG)以及反之亦然的计算模型，则相机被辐射校准。我们的方法利用了在颜色校正后像素值的排序基本保持不变的观察结果。我们表明，这种观测是获得紧凑和稳健的辐射定标模型的关键。由于我们的方法需要的变量更少，所以可以用更少的校准数据来求解。另一个优点是，我们可以从一对RAW-JPEG图像中派生出相机管道。实验表明，我们的方法提供了最先进的结果(特别是最有趣的从JPEG到RAW的转换)。
Raw images are more useful than JPEG images for machine vision algorithms and professional photographers because raw images preserve a linear relation between pixel values and the light measured from the scene. A camera is radiometrically calibrated if there is a computational model which can predict how the raw image is mapped to the corresponding rendered image (e.g. JPEGs) and vice versa. Our method makes use of the observation that the rank order of pixel values are mostly preserved post color correction. We show that this observation is the key for getting a compact and robust radiometric calibration model. Since our method requires fewer variables, it can be solved for using less calibration data. An additional advantage is that we can derive the camera pipeline from a single pair of raw-JPEG images. Experiments demonstrate that our method delivers state-of-the-art results (especially for the most interesting conversion from JPEG to raw).