TY - JOUR
T1 - MP2020
T2 - Visual quality assessment database for macro photography images
AU - Sang, Qingbing
AU - Cao, Yujie
AU - Liu, Lixiong
AU - Hu, Cong
AU - Wu, Xiaojun
N1 - Publisher Copyright:
© 2021 The Authors. IET Image Processing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
PY - 2022/3
Y1 - 2022/3
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85103973883
U2 - 10.1049/ipr2.12198
DO - 10.1049/ipr2.12198
M3 - Article
AN - SCOPUS:85103973883
SN - 1751-9659
VL - 16
SP - 985
EP - 991
JO - IET Image Processing
JF - IET Image Processing
IS - 4
ER -