Bionic vision improves the performances of super resolution imaging

Yuqing Xiao, Jie Cao*, Zihan Wang, Qun Hao, Haoyong Yu, Qiang Luo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A novel super resolution reconstruction method is proposed to improve super resolution image performances. The proposed method uses bionic vision sampling model to obtain low resolution images and performs super resolution reconstruction in logarithmic polar coordinates. We carry out comparative experiments between the proposed method and the traditional method in terms of Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Mean Squared Error (MSE). The results show that the performances of proposed method are better than that of the traditional method. Especially the SSIM of global image (butterfly), the proposed method is 34.45% higher than the traditional method.

Original languageEnglish
Title of host publicationTenth International Symposium on Precision Engineering Measurements and Instrumentation
EditorsJie Lin, Jiubin Tan
PublisherSPIE
ISBN (Electronic)9781510627819
DOIs
Publication statusPublished - 2019
Event10th International Symposium on Precision Engineering Measurements and Instrumentation, ISPEMI 2018 - Kunming, China
Duration: 8 Aug 201810 Aug 2018

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11053
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference10th International Symposium on Precision Engineering Measurements and Instrumentation, ISPEMI 2018
Country/TerritoryChina
CityKunming
Period8/08/1810/08/18

Keywords

  • PSNR
  • SSIM
  • bionic vision
  • super resolution

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