[an error occurred while processing this directive]

ZTE Communications ›› 2019, Vol. 17 ›› Issue (1): 38-47.DOI: 10.12142/ZTECOM.201901007

• • 上一篇    下一篇

  

  • 收稿日期:2018-06-09 出版日期:2019-02-20 发布日期:2019-11-14

Perceptual Quality Assessment of Omnidirectional Images: Subjective Experiment and Objective Model Evaluation

DUAN Huiyu, ZHAI Guangtao, MIN Xiongkuo, ZHU Yucheng, FANG Yi, YANG Xiaokang   

  1. Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2018-06-09 Online:2019-02-20 Published:2019-11-14
  • About author:DUAN Huiyu (huiyuduan@sjtu.edu.cn) received the B.E. degree from the University of Electronic Science and Technology of China in 2017. He is currently pursuing the Ph.D. degree at the Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, China. His research interests include image quality assessment, visual attention modeling, and perceptual signal processing.|ZHAI Guangtao received the B.E. and M.E. degrees from Shandong University, China in 2001 and 2004, respectively, and the Ph.D. degree from Shanghai Jiao Tong University, China in 2009. From 2008 to 2009, he was a visiting student with the Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada, where he was a post-doctoral fellow from 2010 to 2012. From 2012 to 2013, he was a Humboldt Research Fellow with the Institute of Multimedia Communication and Signal Processing, Friedrich Alexander University of Erlangen-Nuremberg, Germany. He is currently a Research Professor with the Institute of Image Communication and Information Processing, Shanghai Jiao Tong University. His research interests include multimedia signal processing and perceptual signal processing. He received the National Excellent Ph.D. Thesis Award from the Ministry of Education of China in 2012.|MIN Xiongkuo received the B.E. degree from Wuhan University, China in 2013, and the Ph.D. degree from Shanghai Jiao Tong University, China in 2018. From 2016 to 2017, he was a visiting student with the Department of Electrical and Computer Engineering, University of Waterloo, Canada. He is currently a post-doctoral fellow with Shanghai Jiao Tong University. His research interests include image quality assessment, visual attention modeling, and perceptual signal processing. He received the Best Student Paper Award from the IEEE ICME 2016.|ZHU Yucheng received the B.E. degree from the Shanghai Jiao Tong University, China in 2015. He is currently pursuing the Ph.D. degree at the Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University. His research interests include image quality assessment, visual attention modeling, and perceptual signal processing. He received Grand Challenge Best Performance Awards in ICME 2017 and 2018.|FANG Yi is an undergraduate student at Shanghai Jiao Tong University, China and will receive the B.E. degree in 2019. She will pursue the M.E. degree at the Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University. Her research interests include image quality assessment, visual attention modeling, and perceptual signal processing.|YANG Xiaokang received the B.S. degree from Xiamen University, China in 1994, the M.S. degree from the Chinese Academy of Sciences, China in 1997, and the Ph.D. degree from Shanghai Jiao Tong University, China in 2000. From 2000 to 2002, he was a Research Fellow with the Centre for Signal Processing, Nanyang Technological University, Singapore. From 2002 to 2004, he was a Research Scientist with the Institute for Infocomm Research, Singapore. From 2007 to 2008, he visited the Institute for Computer Science, University of Freiburg, Freiburg im Breisgau, Germany, as an Alexander von Humboldt Research Fellow. He is currently a Distinguished Professor with the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, where he is also the Deputy Director of the Institute of Image Communication and Information Processing. His current research interests include image processing and communication, computer vision, and machine learning.

RichHTML

PDF

Abstract:

Virtual reality (VR) environment can provide immersive experience to viewers. Under the VR environment, providing a good quality of experience is extremely important. Therefore, in this paper, we present an image quality assessment (IQA) study on omnidirectional images. We first build an omnidirectional IQA (OIQA) database, including 16 source images with their corresponding 320 distorted images. We add four commonly encountered distortions. These distortions are JPEG compression, JPEG2000 compression, Gaussian blur, and Gaussian noise. Then we conduct a subjective quality evaluation study in the VR environment based on the OIQA database. Considering that visual attention is more important in VR environment, head and eye movement data are also tracked and collected during the quality rating experiments. The 16 raw and their corresponding distorted images, subjective quality assessment scores, and the head-orientation data and eye-gaze data together constitute the OIQA database. Based on the OIQA database, we test some state-of-the-art full-reference IQA (FR-IQA) measures on equirectangular format or cubic format omnidirectional images. The results show that applying FR-IQA metrics on cubic format omnidirectional images could improve their performance. The performance of some FR-IQA metrics combining the saliency weight of three different types are also tested based on our database. Some new phenomena different from traditional IQA are observed.

Key words: perceptual quality assessment, omnidirectional images, subjective experiment, objective model evaluation, visual saliency