• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Wang, Xuejin (Wang, Xuejin.) | Jiang, Qiuping (Jiang, Qiuping.) | Shao, Feng (Shao, Feng.) | Gu, Ke (Gu, Ke.) | Zhai, Guangtao (Zhai, Guangtao.) | Yang, Xiaokang (Yang, Xiaokang.)

收录:

EI Scopus SCIE

摘要:

Tone mapping operators (TMOs) are developed to convert a high dynamic range (HDR) image into a low dynamic range (LDR) one for display with the goal of preserving as much visual information as possible. However, image quality degradation is inevitable due to the dynamic range compression during the tone-mapping process. This accordingly raises an urgent demand for effective quality evaluation methods to select a high-quality tone-mapped image (TMI) from a set of candidates generated by distinct TMOs or the same TMO with different parameter settings. A key element to the success of TMI quality evaluation is to extract effective features that are highly consistent with human perception. Towards this end, this paper proposes a novel blind TMI quality metric by exploiting both local degradation characteristics and global statistical properties for feature extraction. Several image attributes including texture, structure, colorfulness and naturalness are considered either locally or globally. The extracted local and global features are aggregated into an overall quality via regression. Experimental results on two benchmark databases demonstrate the superiority of the proposed metric over both the state-of-the-art blind quality models designed for synthetically distorted images (SDIs) and the blind quality models specifically developed for TMIs.

关键词:

Standards tone-mapped image Degradation high dynamic range multi-resolution statistics Dynamic range Quality assessment Distortion Feature extraction no reference multi-scale statistics Image quality

作者机构:

  • [ 1 ] [Wang, Xuejin]Ningbo Univ, Fac Informat Sci & Engn, Ningbo 315211, Peoples R China
  • [ 2 ] [Jiang, Qiuping]Ningbo Univ, Fac Informat Sci & Engn, Ningbo 315211, Peoples R China
  • [ 3 ] [Shao, Feng]Ningbo Univ, Fac Informat Sci & Engn, Ningbo 315211, Peoples R China
  • [ 4 ] [Gu, Ke]Beijing Univ Technol, Beijing Adv Innovat Ctr Future Internet Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing 100124, Peoples R China
  • [ 5 ] [Zhai, Guangtao]Shanghai Jiao Tong Univ, Inst Image Commun & Network Engn, Shanghai 200240, Peoples R China
  • [ 6 ] [Yang, Xiaokang]Shanghai Jiao Tong Univ, Inst Image Commun & Network Engn, Shanghai 200240, Peoples R China

通讯作者信息:

  • [Shao, Feng]Ningbo Univ, Fac Informat Sci & Engn, Ningbo 315211, Peoples R China

查看成果更多字段

相关关键词:

来源 :

IEEE TRANSACTIONS ON MULTIMEDIA

ISSN: 1520-9210

年份: 2021

卷: 23

页码: 692-705

7 . 3 0 0

JCR@2022

ESI学科: COMPUTER SCIENCE;

ESI高被引阀值:87

JCR分区:1

被引次数:

WoS核心集被引频次: 2

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 0

归属院系:

在线人数/总访问数:488/4963026
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司