论文标题
内容感知的自动参数调整近似颜色变换
Content-Aware Automated Parameter Tuning for Approximate Color Transforms
论文作者
论文摘要
文献中报道了许多近似颜色变换，旨在通过不知不觉地更改显示图像的颜色内容来减少显示功耗。要实用，这些技术需要在选择转换参数以保持感知质量时具有内容感知。这项工作提出了一种计算效率的方法，用于根据要转换的内容来计算近似颜色变换参数的参数下限。我们对62名参与者和6,400个图像对比较进行了用户研究，以得出所提出的解决方案。我们使用用户研究结果通过使用简单的基于图像色的启发式方法，以1.6％的平均平方误差可靠地预测该下限。我们表明，这些启发式方法具有Pearson和Spearman等级相关系数大于0.7（P <0.01），并且我们的模型超出了用户研究的数据。用户研究结果还表明，颜色变换能够在大多数用户报告可忽略的视觉障碍的情况下最多可节省50％的动力。
There are numerous approximate color transforms reported in the literature that aim to reduce display power consumption by imperceptibly changing the color content of displayed images. To be practical, these techniques need to be content-aware in picking transformation parameters to preserve perceptual quality. This work presents a computationally-efficient method for calculating a parameter lower bound for approximate color transform parameters based on the content to be transformed. We conduct a user study with 62 participants and 6,400 image pair comparisons to derive the proposed solution. We use the user study results to predict this lower bound reliably with a 1.6% mean squared error by using simple image-color-based heuristics. We show that these heuristics have Pearson and Spearman rank correlation coefficients greater than 0.7 (p<0.01) and that our model generalizes beyond the data from the user study. The user study results also show that the color transform is able to achieve up to 50% power saving with most users reporting negligible visual impairment.
