多视点视频编码去相关颜色校正

多视点视频编码效率受到各个视点图像之间颜色不均衡的影响。在三色激励值近似线性无关的lαβ颜色空间中，对多视点视频数据实现了颜色校正。根据视频序列原始数据的特点，选择合适的变换矩阵，提供了YUV到lαβ空间的变换式。为降低不同视点间亮度差异的影响，在块搜索和匹配中结合相关分析法，获取最优匹配块。将匹配块数据变换到从lαβ衍生的一个线性无关的颜色空间中，采用统计量逼近的方法对数据进行了更简便的校正。结果表明，所校正的数据变换回YUV空间后，主观效果良好，消除了颜色差异，在编码性能上，Y分量平均PSNR提高达l.4dB以上，证明了该颜色校正算法的有效性。

De-correlated color correction for multiview video coding

The efficiency of multiview video coding is influenced by the color discrepancies of pictures in different views. A new color correction method was proposed for multiview videos in the lαβ color space whose tristimulus values were approximately irrelevant to each other. According to the characteristics of the original data of multiview videos, the appropriate transformation matrices were selected to provide formula for transforming data from YUV to lαβ color space. In order to mitigate the influence of illumination change between different views, correlation analysis was integrated in block-matching to search for the best matching blocks. The data of these blocks was transformed into a de-correlated color space derived from lαβ, and corrected with a statistic approaching method in a more convenient way. The results show that the subjective effect is satisfactory with the elimination of color discrepancies after color correction, and in terms of coding efficiency, the average PSNR of Y component is up to 1.4dB, which proves the effectiveness of this color correction method.