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A Robust Algorithm for Color Correction between Two Stereo Images

机译:一种鲁棒的两个立体图像之间的色彩校正算法

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Most multi-camera vision applications assume a single common color response for all cameras. However, significant luminance and chrominance discrepancies among different camera views often exist due to the dissimilar radiometric characteristics of different cameras and the variation of lighting conditions. These discrepancies may severely affect the algorithms that depend on the color correspondence. To address this problem, this paper proposes a robust color correction algorithm. Instead of handling the image as a whole or employing a color calibration object, we compensate for the color discrepancies region by region. The proposed algorithm can avoid the problem that the global correction techniques possiblely give bad correction results in local areas of an image. Many experiments have been done to prove the effectiveness and the robustness of our algorithm. Though we formulate the algorithm in the context of stereo vision, it can be extended to other applications in a straightforward way.
机译:大多数多摄像机视觉应用程序对所有摄像机都采用单一的通用色彩响应。但是,由于不同摄像机的放射线特性不同以及照明条件的变化,经常会在不同摄像机视图之间存在明显的亮度和色度差异。这些差异可能严重影响依赖于颜色对应关系的算法。为了解决这个问题,本文提出了一种鲁棒的色彩校正算法。代替整体上处理图像或使用颜色校准对象,我们逐个区域补偿颜色差异。提出的算法可以避免全局校正技术可能在图像局部区域给出较差的校正结果的问题。已经进行了许多实验以证明我们算法的有效性和鲁棒性。尽管我们在立体视觉的背景下制定了该算法,但可以将其直接扩展到其他应用程序。

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