NDLI: A novel SVD-based image quality assessment metric

Content Provider	IEEE Xplore Digital Library
Author	Shuigen Wang Chenwei Deng Weisi Lin Baojun Zhao Jie Chen
Copyright Year	2013
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore (Jie Chen) \|\| Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore (Weisi Lin) \|\| Sch. of Inf. & Electron., Beijing Inst. of Technol., Beijing, China (Shuigen Wang; Chenwei Deng; Baojun Zhao)
Abstract	Image distortion can be categorized into two aspects: content-dependent degradation and content-independent one. An existing full-reference image quality assessment (IQA) metric cannot deal with these two different impacts well. Singular value decomposition (SVD) as a useful mathematical tool has been used in various image processing applications. In this paper, SVD is employed to separate the structural (content-dependent) and the content-independent components. For each portion, we design a specific assessment model to tailor for its corresponding distortion properties. The proposed models are then fused to obtain the final quality score. Experimental results with the TID database demonstrate that the proposed metric achieves better performance in comparison with the relevant state-of-the-art quality metrics.
Starting Page	423
Ending Page	426
File Size	1076845
Page Count	4
File Format	PDF
ISBN	9781479923410
DOI	10.1109/ICIP.2013.6738087
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-15
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Image quality Degradation PSNR Visualization Distortion Singular Value Decomposition Image Quality Assessment Human Visual System
Content Type	Text
Resource Type	Article

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