MP2020: Visual quality assessment database for macro photography images

  • Qingbing Sang*
  • , Yujie Cao
  • , Lixiong Liu
  • , Cong Hu
  • , Xiaojun Wu
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

With the development of mobile phone camera technology, mobile phones can take a large number of macro photography images that previously could only be taken by professional cameras. Therefore, it is of great significance to study the quality of macro photography images. For this reason, a macro photography image visual quality evaluation database is established and it is named as MP2020. The database contains 100 reference images and 800 distorted images of four distortion types, including 200 distorted images of JPEG 2000, 200 distorted images of JPEG, 200 distorted images of white noise, and 200 distorted images of Gaussian blur. The DMOS values in the database were calculated from 48000 data which are provided by 60 subjects. Ten classical image quality assessment algorithms were tested on the MP2020 database. The experimental results show that the existing image quality assessment algorithms, which are widely used, are not applicable to the macro photography images. Therefore, MP2020 would contribute to the improvement of existing algorithms and the development of new algorithms. MP2020 has been uploaded to GitHub for download.

Original languageEnglish
Pages (from-to)985-991
Number of pages7
JournalIET Image Processing
Volume16
Issue number4
DOIs
Publication statusPublished - Mar 2022
Externally publishedYes

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