Liu Qi, Yuan Hui, Hamzaoui Raouf, Su Honglei, Hou Junhui, Yang Huan
IEEE Trans Image Process. 2021;30:6623-6636. doi: 10.1109/TIP.2021.3096060. Epub 2021 Jul 26.
In rate-distortion optimization, the encoder settings are determined by maximizing a reconstruction quality measure subject to a constraint on the bitrate. One of the main challenges of this approach is to define a quality measure that can be computed with low computational cost and which correlates well with the perceptual quality. While several quality measures that fulfil these two criteria have been developed for images and videos, no such one exists for point clouds. We address this limitation for the video-based point cloud compression (V-PCC) standard by proposing a linear perceptual quality model whose variables are the V-PCC geometry and color quantization step sizes and whose coefficients can easily be computed from two features extracted from the original point cloud. Subjective quality tests with 400 compressed point clouds show that the proposed model correlates well with the mean opinion score, outperforming state-of-the-art full reference objective measures in terms of Spearman rank-order and Pearson linear correlation coefficient. Moreover, we show that for the same target bitrate, rate-distortion optimization based on the proposed model offers higher perceptual quality than rate-distortion optimization based on exhaustive search with a point-to-point objective quality metric. Our datasets are publicly available at https://github.com/qdushl/Waterloo-Point-Cloud-Database-2.0.
在率失真优化中，编码器设置是通过在比特率受限的条件下最大化重建质量度量来确定的。这种方法的主要挑战之一是定义一种可以以低计算成本计算且与感知质量相关性良好的质量度量。虽然已经为图像和视频开发了几种满足这两个标准的质量度量，但对于点云来说并不存在这样的度量。我们通过提出一种线性感知质量模型来解决基于视频的点云压缩（V-PCC）标准的这一局限性，该模型的变量是V-PCC几何和颜色量化步长，其系数可以很容易地从原始点云提取的两个特征中计算出来。对400个压缩点云进行的主观质量测试表明，所提出的模型与平均意见得分相关性良好，在斯皮尔曼等级顺序和皮尔逊线性相关系数方面优于现有的全参考客观度量。此外，我们表明，对于相同的目标比特率，基于所提出模型的率失真优化比基于逐点客观质量度量的穷举搜索的率失真优化提供更高的感知质量。我们的数据集可在https://github.com/qdushl/Waterloo-Point-Cloud-Database-2.0上公开获取。
