| 富振奇,费延佳,杨艳,邵枫.基于深层特征学习的无参考立体图像质量评价[J].光电子激光,2018,29(5):545~552 |
| 基于深层特征学习的无参考立体图像质量评价 |
| No-reference stereoscopic image quality assessment based on deep feature learni ng |
| 投稿时间：2017-08-24 |
| DOI： |
| 中文关键词: 卷积神经网络(CNN) 立体图像 质量评价 双目视觉 |
| 英文关键词:convolutional neural network stereoscopic image quality assessment binocular vision |
| 基金项目:国家自然科学基金(61622109)资助项目 (宁波大学 信息科学与工程学院,浙江 宁波 315211) |
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| 摘要点击次数: 1330 |
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| 中文摘要: |
| 提出了一种基于深层特征学习的无参考(NR)立体图 像质量评价方 法。与传统人工提取图像特征不同,采用卷积神经网络(CNN)自动提取图像特征,评价过程 分为训练和 测试两阶段。在训练阶段,将图像分块训练CNN网络,利用CNN提取图像块特征,并结合不同 的整合方式 得到图像的全局特征,通过支持向量回归(SVR)建立主观质量与全局特征的回归模型；在测 试阶段,由已训练的CNN网 络和回归模型,得到左右图像和独眼图的质量。最后,根据人眼双目视觉特性融合左图像、 右图像和独眼 图的质量,得到立体图像质量。本文方法在LIVE-I和LIVE-II数据库上的Spearman等级系 数(SROCC)分别达 到了0.94,评价结果准确,与人眼的主 观感受一致。 |
| 英文摘要: |
| In this paper,we propose a new m ethod for stereoscopic image quality assessment based on deep feature learning.Different from traditional stereoscop ic image quality evaluation methods,we use convolutional neural network (CNN) to extract features,and the quality prediction process can be divided into two steps:training and testing.I n the training phase,the images are divided into blocks to train the CNN network and then the block features can be extracted by the CNN.Through differe nt integration ways,global features of images are calculated from block features.We establish the regres sion model between subjective scoring values and global features by support vector regression (SVR).In the tes t phase,quality scores of left,right and cyclopean images can be predicted according to the trained CNN network and regression model.Finally, the qualities of left,right and cyclopean images are combined together to get the stereoscopic image quality.Ex perimental results on the publicly available LIVE-I and LIVE-II data sets demonstrate the superiority of the prop osed method.The spearman rankorder correlation coefficient (SROCC) scores of our method in the LIVE-I and LIVE-II reach 0.94and 0.89respectively.The eva luation results are accurate and consistent with the subjective perception of the human eyes. |
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