基于三维与二维联合的彩色点云无参考质量评价方法
PDF下载 (112)刘佳语,蒋志迪,郁 梅.基于三维与二维联合的彩色点云无参考质量评价方法[J].宁波大学学报(理工版),2024,37(4):84-94.DOI:10.20098/j.cnki.1001-5132.2023.1115
LIU Jiayu,JIANG Zhidi,YU Mei.No-reference quality assessment method of color point cloud based on the combination of 3D and 2D information[J].Journal of Ningbo University(Natural Science & Engineering Edition),2024,37(4):84-94.DOI:10.20098/j.cnki.1001-5132.2023.1115
| Title: | No-reference quality assessment method of color point cloud based on the combination of 3D and 2D information |
| 作者: | 刘佳语, 蒋志迪, 郁 梅 |
| Author(s): | LIU Jiayu, JIANG Zhidi, YU Mei |
| 关键词: | 彩色点云; 质量评价; 三维与二维联合; 感知特征 |
| Keywords: | color point cloud; quality assessment; combination of 3D and 2D; perceptual feature |
| 分类号: | TP37 |
| DOI: | 10.20098/j.cnki.1001-5132.2023.1115 |
| 文献标识码: | A |
| 摘要: | 点云作为一种三维视觉信息的载体, 在其采集、传输和重建时会不可避免地引入失真, 降低点云的视觉质量, 因此需要有效方法对失真点云进行质量评价. 本文提出一种基于三维与二维联合的彩色点云无参考质量评价方法, 在三维、二维空间中分别提取点云的几何信息和彩色纹理信息; 在点云几何与彩色纹理的联合失真方面, 新方法对几何和彩色纹理投影图进行联合张量分解; 考虑到人眼多方向、多尺度的感知特征, 利用曲波变换在彩色纹理投影图上提取特征; 最后通过随机森林池化来预测彩色点云的质量. 在3个数据库上的实验结果表明, 本文方法优于现有一些点云质量评价方法, 其预测结果与主观质量具有良好的相关性. |
| Abstract: | As a carrier of 3D visual information, point clouds inevitably exhibit distortions that are introduced during their acquisition, transmission, and reconstruction, leading to a reduction in their visual quality. Therefore, it is necessary to effectively measure the quality of distorted point clouds. This paper proposes a no-reference quality assessment method of color point cloud based on the combination of 3D and 2D information, with which the geometric information and color texture information of point clouds in 3D and 2D spaces are extracted, respectively. To account for the combined distortion of geometry and color texture in point clouds, a tensor decomposition-based approach is applied to jointly analyze and extract features from the combination of these two projection maps. Considering the multi-directional and multi-scale perceptual characteristics of the human eye, a curvelet transform is used to extract features from the color texture projection map. Finally, a random forest pooling method is employed to predict the quality of color point clouds. Experimental results on three databases demonstrate that the proposed method outperforms some of the existing point cloud quality assessment methods, in that it shows better correlation between the predicted results and subjective quality assessment. |
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| 备注/Memo: | 收稿日期: 2023−11−08. 宁波大学学报（理工版）网址: http://journallg.nbu.edu.cn/ 基金项目: 浙江省自然科学基金（LY21F010003）. 第一作者: 刘佳语, 硕士研究生, 主要研究方向: 点云质量评价. E-mail: liujiayu971089837@163.com *通信作者: 郁梅, 博士/教授, 主要研究方向: 三维视频处理与编码、图像与视频质量评价. E-mail: yumei@nbu.edu.cn 宁波大学学报（理工版）网址：http://journallg.nbu.edu.cn/ |
