jist0416-fasttrack_1560771380502 published june 2019.pdf (1.52 MB)
A full-reference image quality assessment for multiply distorted image based on visual mutual information
journal contribution
posted on 2023-06-09, 18:28 authored by Yin Zhang, Bai Xuehan, Junhua Yan, Yongqi Xiao, Wanyi Zhang, Chris ChatwinChris Chatwin, Rupert YoungRupert YoungA full-reference image quality assessment (FR-IQA) method for multi-distortion based on visual mutual information (MD-IQA) is proposed to solve the problem that the existing FR-IQA methods are mostly applicable to single-distorted images, but the assessment result for multiply distorted images is not ideal. First, the reference image and the distorted image are preprocessed by steerable pyramid decomposition and contrast sensitivity function (CSF). Next, a Gaussian scale mixture (GSM) model and an image distorted model are respectively constructed for the reference images and the distorted images. Then, visual distorted models are constructed both for the reference images and the distorted images. Finally, the mutual information between the processed reference image and the distorted image is calculated to obtain the full-reference quality assessment index for multiply distorted images. The experimental results show that the proposed method has higher accuracy and better performance for multiply distorted images.
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Publication status
- Published
File Version
- Published version
Journal
Journal of Imaging Science and TechnologyISSN
1062-3701Publisher
Society for Imaging Science and TechnologyDepartment affiliated with
- Engineering and Design Publications
Research groups affiliated with
- Industrial Informatics and Signal Processing Research Group Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2019-07-22First Open Access (FOA) Date
2019-07-22First Compliant Deposit (FCD) Date
2019-07-19Usage metrics
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