Study of no-reference image quality assessment algorithms on printed images

被引:5
|
作者
Eerola, Tuomas [1 ]
Lensu, Lasse [1 ]
Kalviainen, Heikki [1 ]
Bovik, Alan C. [2 ]
机构
[1] Lappeenranta Univ Technol, Dept Math & Phys, Lappeenranta 53850, Finland
[2] Univ Texas Austin, Dept Elect & Comp Engn, Austin, TX 78712 USA
基金
美国国家科学基金会;
关键词
print quality; image quality assessment; no reference; STATISTICS;
D O I
10.1117/1.JEI.23.6.061106
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Measuring the visual quality of printed media is important since printed products have an important role in everyday life. Finding ways to automatically predict the image quality has been an active research topic in digital image processing, but adapting those methods to measure the visual quality of printed media has not been studied often or in depth and is not straightforward. Here, we analyze the efficacy of no-reference image quality assessment (IQA) algorithms originally developed for digital IQA with regards to predicting the perceived quality of printed natural images. We perform a comprehensive statistical comparison of the methods. The best methods are shown to accurately predict subjective opinions of the quality of printed photographs using data from a psychometric study. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
引用
收藏
页数:12
相关论文
共 50 条
  • [31] No-reference image quality assessment of authentically distorted images with global and local statistics
    Rajchel, Milosz
    Oszust, Mariusz
    SIGNAL IMAGE AND VIDEO PROCESSING, 2021, 15 (01) : 83 - 91
  • [32] No-reference image quality assessment for images degraded by color quantization in HSV Space
    De, Kanjar
    Masilamani, V
    PROCEEDINGS OF THE 2016 IEEE STUDENTS' TECHNOLOGY SYMPOSIUM (TECHSYM), 2016, : 40 - 45
  • [33] A Brief Survey on No-Reference Image Quality Assessment Methods for Magnetic Resonance Images
    Stepien, Igor
    Oszust, Mariusz
    JOURNAL OF IMAGING, 2022, 8 (06)
  • [34] No-reference image quality assessment for confocal endoscopy images with perceptual local descriptor
    Dong, Xiangjiang
    Fu, Ling
    Liu, Qian
    JOURNAL OF BIOMEDICAL OPTICS, 2022, 27 (05)
  • [35] An image response framework for no-reference image quality assessment
    Sun, Tongfeng
    Ding, Shifei
    Xu, Xinzheng
    COMPUTERS & ELECTRICAL ENGINEERING, 2018, 70 : 764 - 776
  • [36] Statistical Evaluation of No-Reference Image Quality Assessment Metrics for Remote Sensing Images
    Li, Shuang
    Yang, Zewei
    Li, Hongsheng
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2017, 6 (05)
  • [37] No-Reference Image Quality Assessment Based on HVS
    Fu, Yan
    Wang, Shengchun
    2016 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C), 2016, : 1093 - 1096
  • [38] No-reference visual quality assessment for image inpainting
    Voronin, V. V.
    Frantc, V. A.
    Marchuk, V. I.
    Sherstobitov, A. I.
    Egiazarian, K.
    IMAGE PROCESSING: ALGORITHMS AND SYSTEMS XIII, 2015, 9399
  • [39] A No-Reference Image Quality Comprehensive Assessment Method
    Fan, Yuan-Yuan
    Sang, Ying-Jun
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2021, 35 (04)
  • [40] No-Reference Quality Assessment for Image Sharpness and Noise
    Tang, Lijuan
    Min, Xiongkuo
    Jakhetiya, Vinit
    Gu, Ke
    Zhang, Xinfeng
    Yang, Shuai
    2016 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA), 2016,