Fine-Grained Quality Assessment for Compressed Images
Fine-Grained Quality Assessment for Compressed Images
复制标题
压缩图像的细粒度质量评估
DOI：
10.1109/tip.2018.2874283
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发表时间：
2019-03
影响因子：
10.6
通讯作者：
Gao Wen
中科院分区：
文献类型：
--
作者：
Zhang Xinfeng;Lin Weisi;Wang Shiqi;Liu Jiaying;Ma Siwei;Gao Wen
由于图像服务的迫切需求，图像质量评价（IQA）越来越受到重视。基于感知的图像压缩是要求IQA指标与人类视觉高度相关的最突出的应用之一。为了探索更符合人类视觉的IQA算法，构建了几个校准数据库。然而，现有数据库中的扭曲图像通常是通过对原始图像进行粗程度的各种扭曲而产生的，因此在这些图像上验证的IQA算法在优化具有细粒度质量差异的基于感知的图像压缩时可能效率低下。在本文中，我们构建了一个大规模的图像数据库，用于压缩图像的细粒度质量评估。在该数据库中，参考图像被采用不同优化方法的JPEG编码器以恒定比特率压缩。为了区分细微差异，在主观实验中采用两两比较法对其进行排序。我们选取了100张参考图像作为数据库，通过4种不同的JPEG优化方法将每张图像压缩为3个目标比特率，总共生成1200张畸变图像。在该数据库上对16种知名的IQA算法进行了评估和分析。通过设计的细粒度IQA数据库，我们希望通过将图像质量评估从粗粒度阶段转移到细粒度阶段来进一步促进图像质量评估。该数据库可在https://sites.google.com/site/zhangxinf07/fg-iqa上获得。
Image quality assessment (IQA) has attracted more and more attention due to the urgent demand in image services. The perceptual-based image compression is one of the most prominent applications that require IQA metrics to be highly correlated with human vision. To explore IQA algorithms that are more consistent with human vision, several calibrated databases have been constructed. However, the distorted images in the existing databases are usually generated by corrupting the pristine images with various distortions in coarse levels, such that the IQA algorithms validated on them may be inefficient to optimize the perceptual-based image compression with fine-grained quality differences. In this paper, we construct a large-scale image database which can be used for fine-grained quality assessment of compressed images. In the proposed database, reference images are compressed at constant bitrate levels by JPEG encoders with different optimization methods. To distinguish subtle differences, the pair-wise comparison method is utilized to rank them in subjective experiments. We select 100 reference images for the proposed database, and each image is compressed into three target bitrates by four different JPEG optimization methods, such that 1200 distorted images are generated in total. Sixteen well-known IQA algorithms are evaluated and analyzed on the proposed database. With the devised fine-grained IQA database, we expect to further promote image quality assessment by shifting it from a coarse-grained stage to a fine-grained stage. The database is available at: https://sites.google.com/site/zhangxinf07/fg-iqa.
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影响因子：
10.6
作者：
Nuutinen, Mikko;Virtanen, Toni;Hakkinen, Jukka
通讯作者：
Hakkinen, Jukka
影响因子：
10.6
作者：
Sheikh, HR;Bovik, AC
通讯作者：
Bovik, AC
影响因子：
2.7
作者：
E. Allen;S. Triantaphillidou;R. E. Jacobson
通讯作者：
E. Allen;S. Triantaphillidou;R. E. Jacobson
DOI：
10.2352/j.imagingsci.technol.(2007)51:3(259
发表时间：
2007-05
影响因子：
1
作者：
S. Triantaphillidou;E. Allen;R. E. Jacobson
通讯作者：
S. Triantaphillidou;E. Allen;R. E. Jacobson
影响因子：
3.9
作者：
Wang, Z;Bovik, AC
通讯作者：
Bovik, AC