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Author:

Zhang, Huiqing (Zhang, Huiqing.) | Li, Yueqing (Li, Yueqing.) | Li, Shuo (Li, Shuo.) | Liu, Yutao (Liu, Yutao.)

Indexed by:

EI Scopus

Abstract:

Virtual reality has many characteristics such as multi-sensation, interactivity, and presence. Virtual reality images, also known as 360-degree panoramic images, provide users with an immersive experience and have been widely used in education, medical, military and many other fields in recent years. 360-degree panoramic images have high resolution and are subject to varying degrees of distortion during transmission and storage. Therefore, the evaluation of virtual reality images has practical significance. To this end, we propose a method for evaluating the quality of images in the new CVIQD database. The proposed image quality assessment model is developed based on Haar wavelet and Db4 wavelet feature extraction and fusion. The method is compared with a single wavelet feature extraction method. Experiments show that the method has better performance. © Published under licence by IOP Publishing Ltd.

Keyword:

Feature extraction Machine learning Image fusion Extraction Military photography Virtual reality Medical imaging User experience Learning algorithms Manufacture Image quality

Author Community:

  • [ 1 ] [Zhang, Huiqing]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Zhang, Huiqing]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 3 ] [Li, Yueqing]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Li, Shuo]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Li, Shuo]Engineering Research Center of Digital Community, Ministry of Education, Beijing; 100124, China
  • [ 6 ] [Liu, Yutao]Graduate School at Shenzhen, Tsinghua University, Shenzhen; 518055, China

Reprint Author's Address:

  • [li, yueqing]faculty of information technology, beijing university of technology, beijing; 100124, china

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Source :

ISSN: 1757-8981

Year: 2019

Issue: 5

Volume: 569

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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