文章基本信息

标题：Content-Aware Retargeted Image Quality Assessment
本地全文：下载
作者：Tingting Zhang ; Tingting Zhang ; Ming Yu 等
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2019
卷号：10
期号：3
页码：111
DOI：10.3390/info10030111
出版社：MDPI Publishing
摘要：In targeting the low correlation between existing image scaling quality assessment methods and subjective awareness, a content-aware retargeted image quality assessment algorithm is proposed, which is based on the structural similarity index. In this paper, a similarity index, that is, a local structural similarity algorithm, which can measure different sizes of the same image is proposed. The Speed Up Robust Feature (SURF) algorithm is used to extract the local structural similarity and the image content loss degree. The significant area ratio is calculated by extracting the saliency region and the retargeted image quality assessment function is obtained by linear fusion. In the CUHK image database and the MIT RetargetMe database, compared with four representative assessment algorithms and other latest four kinds of retargeted image quality assessment algorithms, the experiment proves that the proposed algorithm has a higher correlation with Mean Opinion Score (MOS) values and corresponds with the result of human subjective assessment.
关键词：content aware; image retarget; content-aware image scaling; image quality assessment; structural similarity content aware ; image retarget ; content-aware image scaling ; image quality assessment ; structural similarity