Kim Seon Joo, Pollefeys Marc
Departmernt of Computer Science, University of North Carolina at Chapel Hill, NC 27539, USA.
IEEE Trans Pattern Anal Mach Intell. 2008 Apr;30(4):562-76. doi: 10.1109/TPAMI.2007.70732.
In many computer vision systems, it is assumed that the image brightness of a point directly reflects the scene radiance of the point. However, the assumption does not hold in most cases due to nonlinear camera response function, exposure changes, and vignetting. The effects of these factors are most visible in image mosaics and textures of 3D models where colors look inconsistent and notable boundaries exist. In this paper, we propose a full radiometric calibration algorithm that includes robust estimation of the radiometric response function, exposures, and vignetting. By decoupling the effect of vignetting from the response function estimation, we approach each process in a manner that is robust to noise and outliers. We verify our algorithm with both synthetic and real data which shows significant improvement compared to existing methods. We apply our estimation results to radiometrically align images for seamless mosaics and 3D model textures. We also use our method to create high dynamic range (HDR) mosaics which are more representative of the scene than normal mosaics.
在许多计算机视觉系统中，人们假定某一点的图像亮度直接反映该点的场景辐射度。然而，由于非线性相机响应函数、曝光变化和渐晕，这种假定在大多数情况下并不成立。这些因素的影响在图像拼接和3D模型纹理中最为明显，其中颜色看起来不一致且存在明显的边界。在本文中，我们提出了一种完整的辐射校准算法，该算法包括对辐射响应函数、曝光和渐晕的稳健估计。通过将渐晕的影响与响应函数估计解耦，我们以一种对噪声和离群值具有鲁棒性的方式处理每个过程。我们用合成数据和真实数据验证了我们的算法，结果表明与现有方法相比有显著改进。我们将估计结果应用于图像的辐射对齐，以实现无缝拼接和3D模型纹理。我们还使用我们的方法创建高动态范围（HDR）拼接，它比普通拼接更能代表场景。
