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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yuming Li Lai-Man Po Xuyuan Xu Litong Feng Fang Yuan Chun-Ho Cheung Kwok-Wai Cheung |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong, China (Yuming Li; Lai-Man Po; Xuyuan Xu; Litong Feng; Fang Yuan) || Dept. of Inf. Syst., City Univ. of Hong Kong, Hong Kong, China (Chun-Ho Cheung) || Dept. of Comput. Sci., Chu Hai Coll. of Higher Educ., Hong Kong, China (Kwok-Wai Cheung) |
| Abstract | In this work, we describe an efficient generalpurpose no-reference (NR) image quality assessment (IQA) algorithm that is based on a new multiscale directional transform (shearlet transform) with a strong ability to localize distributed discontinuities. The algorithm relies on utilizing the sum of subband coefficient amplitudes (SSCA) as primary features to describe the behavior of natural images and distorted images. Then, stacked autoencoders are applied to exaggerate the discriminative parts of the primary features. Finally, by translating the NR-IQA problem into classification problem, the differences of evolved features are identified by softmax classifier. The resulting algorithm, which we name SESANIA (ShEarlet and Stacked Autoencoders based No-reference Image quality Assessment), is tested on several databases (LIVE, Multiply Distorted LIVE and TID2008) and shown to be suitable to many common distortions, consistent with subjective assessment and comparable to full-reference IQA methods and state-of-the-art general purpose NR-IQA algorithms. |
| Starting Page | 1594 |
| Ending Page | 1597 |
| File Size | 470101 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781479983919 |
| DOI | 10.1109/ISCAS.2015.7168953 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-24 |
| Publisher Place | Portugal |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Databases Image quality Transforms Distortion Feature extraction Transform coding Quality assessment Softmax classification No-reference image quality assessment Shearlet transform Stacked autoencoders |
| Content Type | Text |
| Resource Type | Article |
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