基于引导调制的彩色点云无参考质量评价方法  

CPC-GM:No-reference quality assessment method of color point cloud based on guided modulation

作　　者：郭小敏 郁梅[1] 宋洋[1] 蒋志迪[1] GUO Xiaomin;YU Mei;SONG Yang;JIANG Zhidi(Faculty of Information Science and Engineering,Ningbo University,Ningbo,Zhejiang 31521l,China)

机构地区：[1]宁波大学信息科学与工程学院,浙江宁波315211

出　　处：《光电子．激光》2023年第7期713-722,共10页Journal of Optoelectronics·Laser

基　　金：国家自然科学基金项目(62071266);浙江省自然科学基金项目(LY21F010003)资助项目。

摘　　要：彩色点云(color point cloud,CPC)作为三维场景和对象的有效描述形式,在虚拟现实、增强现实等许多领域得到重要应用。CPC在其采集、压缩、传输、重建等过程中会引入相应的失真,需要设计有效的评价方法对失真CPC质量进行评测。本文提出一种基于引导调制的CPC无参考质量评价方法。考虑到几何信息与彩色纹理信息的联合失真,利用引导调制的方法联立两者,以综合考虑几何失真、彩色纹理失真、联合失真。结合人眼的多通道性,利用剪切波变换提取特征。最后,将所有特征构成的特征向量输入到支持向量回归模型(support vector regression,SVR)学习预测点云质量。实验结果表明,所提出的方法与人类主观感知具有很好的一致性。As an effective description of 3D scenes and objects,color point clouds(CPCs)are widely used in many fields such as virtual reality and augmented reality.However,distortions will be introduced to CPC in the process of its collection,compression,transmission and reconstruction,so it is necessary to design an effective assessment method to evaluate the quality of distorted CPC.In this paper,a no-reference quality assessment method is proposed for CPC based on guided modulation.Considering the joint distortion of geometric information and color texture information,the guided modulation is used to combine them to comprehensively consider geometric distortion,color texture distortion and the joint distortion.Combined with the multi-channel characteristic of human eyes,Shearlet transform is used to extract features.Finally,the feature vector composed of all extracted features is inputted into the support vector regression(SVR)model to learn and predict the quality of point cloud.Experimental results show that the proposed method is well consistent with human subjective perception.

关 键 词：彩色点云(CPC) 无参考质量评价 引导调制 剪切波变换 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]