Abstract
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.
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Wang, Q., Sun, X., Wang, Z. (2010). A Robust Algorithm for Color Correction between Two Stereo Images. In: Zha, H., Taniguchi, Ri., Maybank, S. (eds) Computer Vision – ACCV 2009. ACCV 2009. Lecture Notes in Computer Science, vol 5995. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12304-7_38
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DOI: https://doi.org/10.1007/978-3-642-12304-7_38
Publisher Name: Springer, Berlin, Heidelberg
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