无参考图像质量评价综述

王志明

doi:10.16383/j.aas.2015.c140404

无参考图像质量评价综述

doi: 10.16383/j.aas.2015.c140404

王志明^1,2

1.
北京科技大学计算机与通信工程学院北京 100083;
2.
材料领域知识工程北京市重点实验室北京 100083

详细信息

作者简介:
王志明北京科技大学计算机与通信工程学院副教授. 主要研究方向为图像复原,图像增强和图像质量评价.E-mail: wangzhiming@tsinghua.org.cn

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出版历程
- 收稿日期: 2014-06-03
- 修回日期: 2015-02-02
- 刊出日期: 2015-06-20

Review of No-reference Image Quality Assessment

WANG Zhi-Ming^1,2

1.
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083;
2.
Beijing Key Laboratory of Knowledge Engineering for Materials Science, Beijing 100083

摘要

摘要: 图像质量对人类视觉信息的获取影响很大, 如何在没有参考图像的情况下准确地评价失真图像的质量是一个关键但又非常困难的问题. 本文回顾了近20年来无参考图像质量评价发展的主要技术. 首先,介绍了这一领域常用的衡量评价算法性能的技术指标,以及几个网上共享的典型图像质量评价数据库; 然后,对各种无参考图像质量评价算法进行详细的分类介绍和特点评析; 最后,基于典型数据库对近几年的一些非特定失真图像质量评价方法进行了性能测试和比较. 目的是为这一领域的研究人员提供一个较为全面的、有价值的文献参考.
- 图像质量评价 /
- 无参考图像质量评价 /
- 相关系数 /
- 模糊 /
- 噪声
Abstract: Image quality has a strong impact on human visual information acquisition. It is a key but difficult task to evaluate the quality of a distorted image without a reference image. This paper reviews the main techniques of no-reference image quality assessment (IQA) developed during the past 20 years. Firstly, some technical indexes for IQA algorithm evaluation and several public IQA databases available on network are introduced. Then, various no-reference IQA algorithms are introduced, sorted and discussed in detail. At last, several non-distortion-specific no-reference IQA algorithms presented in recent years are tested and compared on a public database. The purpose of this paper is to provide an integrated and valuable reference for no-reference IQA research.
- Image quality assessment (IQA) /
- no-reference image quality assessment (NR-IQA) /
- correlation coefficient /
- blur /
- noise

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参考文献(153)

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