Proceedings ArticleDOI
Scalable image quality assessment based on structural vectors
Manish Narwaria,Weisi Lin +1 more
- pp 1-6
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TLDR
This paper proposes the use of singular vectors out of Singular Value Decomposition as effective structuring elements in images and use them to quantify the loss in structural information in images.Abstract:
Image quality assessment is useful in many visual processing systems and a great deal of research effort has been put in during the recent years to develop objective image quality metrics that correlate well with the perceived quality measurement. Assessing visual quality of images is not easy since the Human Visual System (HVS) is complicated and difficult to be modelled. It is well known that the HVS is sensitive to spatial frequencies and structure in images, so accounting for structure degradation in images is essential for effective picture quality prediction. In this paper, we propose the use of singular vectors out of Singular Value Decomposition as effective structuring elements in images and use them to quantify the loss in structural information in images. The scalability of the proposed metric has been also explored since singular vectors are ordered according to their visual significance. The proposed metric has been validated convincingly on three independent databases (a total of 1196 images of different distortion types and extents), and found to outperform the relevant existing image quality metrics in literature with all circumstances.read more
Citations
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Journal ArticleDOI
Perceptual visual quality metrics: A survey
Weisi Lin,C.-C. Jay Kuo +1 more
TL;DR: A systematic, comprehensive and up-to-date review of perceptual visual quality metrics (PVQMs) to predict picture quality according to human perception.
Journal ArticleDOI
ViS3: an algorithm for video quality assessment via analysis of spatial and spatiotemporal slices
Phong V. Vu,Damon M. Chandler +1 more
TL;DR: This work presents a VQA algorithm that estimates quality via separate estimates of perceived degradation due to spatial distortion and joint spatial and temporal distortion, and demonstrates that this algorithm performs well in predicting video quality and is competitive with current state-of-the-art V QA algorithms.
Journal ArticleDOI
SVD-Based Quality Metric for Image and Video Using Machine Learning
Manish Narwaria,Weisi Lin +1 more
TL;DR: The two-stage process and the relevant work in the existing visual quality metrics are first introduced followed by an in-depth analysis of SVD for visual quality assessment, which shows the proposed method outperforms the eight existing relevant schemes.
Journal ArticleDOI
Fourier Transform-Based Scalable Image Quality Measure
TL;DR: A new image quality assessment algorithm based on the phase and magnitude of the 2-D discrete Fourier transform that is overall better than several of the existing full-reference algorithms and two RR algorithms and further scalable for RR scenarios.
Journal ArticleDOI
Image Quality Assessment by Visual Gradient Similarity
Jieying Zhu,Nengchao Wang +1 more
TL;DR: Experimental results show that VGS is competitive with state-of-the-art metrics in terms of prediction precision, reliability, simplicity, and low computational cost.
References
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Journal ArticleDOI
Image quality assessment: from error visibility to structural similarity
TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Journal ArticleDOI
A universal image quality index
Zhou Wang,Alan C. Bovik +1 more
TL;DR: Although the new index is mathematically defined and no human visual system model is explicitly employed, experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error.
Image Quality Assessment: From Error Measurement to Structural Similarity
TL;DR: A Structural Similarity Index is developed and its promise is demonstrated through a set of intuitive ex- amples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000.
Book
Modern image quality assessment
Zhou Wang,A.C. Bovik +1 more
TL;DR: This book is about objective image quality assessment to provide computational models that can automatically predict perceptual image quality and to provide new directions for future research by introducing recent models and paradigms that significantly differ from those used in the past.
Proceedings ArticleDOI
Why is image quality assessment so difficult
TL;DR: In this paper, insights on why image quality assessment is so difficult are provided by pointing out the weaknesses of the error sensitivity based framework and a new philosophy in designing image quality metrics is proposed.