Open AccessNo-reference Image Quality Assessment Based on Regional Information
Author(s) -
Tong Peng,
Jing Dong,
Qinhang Li,
Kun He
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/790/1/012106
Subject(s) - computer science , artificial intelligence , image (mathematics) , image quality , quality (philosophy) , computer vision , identity (music) , pattern recognition (psychology) , quality assessment , divisibility rule , human visual system model , data mining , mathematics , evaluation methods , engineering , physics , philosophy , epistemology , discrete mathematics , acoustics , reliability engineering
Human vision can quickly assess the quality of images because of the identity in a region and the divisibility between different regions. According to human visual characteristics, we propose a method of image quality assessment without reference information. Firstly, the image was segmented into a series of homogenous regions. Secondly, we analyzed statistical characteristics for each region. Lastly, the assessment model was constructed according to the statistical differences among regions. The results experimented on the LIVE database II show that this method is competitive to SSIM and PSNR.