NDLI: No-reference image quality assessment via structural information fluctuation

Content Provider	IET Digital Library
Author	Yang, Xichen Wang, Tianshu Ji, Genlin
Abstract	Image quality assessment (IQA) is a meaningful research topic to meet the increasing demand of high-quality image. The degradation of image quality will cause changes in image structural information. Meanwhile, human visual system is sensitive to changes in structural information. This finding motivates us to utilise structural information for proposing IQA method which is consistent with human visual perception. Recently, IQA methods are mainly focused on individual image type, e.g. natural image or screen content image (SCI), thus, the authors proposed a novel no-reference IQA method which can be suitable for both natural image and SCI. The proposed method is based on structural information analysis. For each image, they first obtain the grey-scale fluctuation maps (GFMs) in four detection directions. After that, the grey-scale fluctuation direction map (GFD) of certain image can be acquired via its GFMs. Based on the GFMs and GFD, the structural features of each image are extracted, and then collected and transformed to feature vectors. Subsequently, the IQA model is trained by support vector regression. The experimental results on the public databases demonstrate the proposed method can predict image quality accurately for both natural image and SCI, and the performance is competitive with prevalent methods.
Starting Page	384
Ending Page	396
Page Count	13
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 2, Feb (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0750
Journal	IET Image Processing
Publisher Date	2019-11-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Feature Extraction GFM Grey-scale Fluctuation Direction Map High-quality Image Human Visual Perception Human Visual System Image Processing Image Recognition Image Structural Information IQA Method IQA Model Knowledge Engineering Technique Meaningful Research Topic Natural Image Reference Image Quality Assessment Regression Analysis SCI Screen Content Image Structural Feature Structural Information Analysis Structural Information Fluctuation Support Vector Machine Visual Perception
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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