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Accurate Information vs. Looks Good: Scientific vs. Preferred Rendering

机译:准确的信息与看起来不错:科学与首选渲染

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Scientists use digital camera data as the input to their analysis of image processing algorithms. In this paper we measured the "engineered color errors" introduced by digital camera color processing. Camera manufactures build their color management systems using the sRGB design standard. Although that sRGB is a guideline in the beginning, the final firmware shows certain liberties taken to make the best preferred rendering of scenes. The ensemble of algorithms that perform the color balance, color enhancement, tone scale, and post-LUT for display and printing, create large discrepancies between the sRGB measurements of the light from the scene, and actual sRGB values in cameras. We measured these discrepancies. These modifications to scene information introduce large changes in spatial information and make computer vision algorithms less accurate. Camera firmware and software modify color separation data for better looking pictures. These modifications need to be removed for accurate scientific scene analysis. We describe a computer program that converts a RAW digital camera file to calibrated file, in which digit value is proportional to log scene radiances.
机译:科学家使用数码相机数据作为它们对图像处理算法分析的输入。在本文中,我们测量了数字相机颜色处理引入的“工程色误差”。相机制造使用SRGB设计标准构建其颜色管理系统。虽然SRGB是一开始的指导,但最终固件显示某些自由以制定最佳首选的场景。执行色彩平衡,色彩增强,色调刻度和LUT后的算法的集合,用于显示和打印后,从场景的光线的SRGB测量和相机中的实际SRGB值之间产生大的差异。我们衡量了这些差异。这些对场景信息的修改引入了空间信息的大量变化,使计算机视觉算法不太准确。相机固件和软件修改颜色分离数据,以便更好地看图片。需要删除这些修改以进行精确的科学场景分析。我们描述了一个计算机程序,该计算机程序将原始数码相机文件转换为校准文件,其中数字值与日志场景adriAnce成比例。

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