Journal ArticleDOI
SVD-Based Quality Metric for Image and Video Using Machine Learning
Manish Narwaria,Weisi Lin +1 more
- Vol. 42, Iss: 2, pp 347-364
TLDR
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.Abstract:
We study the use of machine learning for visual quality evaluation with comprehensive singular value decomposition (SVD)-based visual features. In this paper, 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. Singular values and vectors form the selected features for visual quality assessment. Machine learning is then used for the feature pooling process and demonstrated to be effective. This is to address the limitations of the existing pooling techniques, like simple summation, averaging, Minkowski summation, etc., which tend to be ad hoc. We advocate machine learning for feature pooling because it is more systematic and data driven. The experiments show that the proposed method outperforms the eight existing relevant schemes. Extensive analysis and cross validation are performed with ten publicly available databases (eight for images with a total of 4042 test images and two for video with a total of 228 videos). We use all publicly accessible software and databases in this study, as well as making our own software public, to facilitate comparison in future research.read more
Citations
More filters
Journal ArticleDOI
No-Reference Image Quality Assessment in the Spatial Domain
TL;DR: Despite its simplicity, it is able to show that BRISQUE is statistically better than the full-reference peak signal-to-noise ratio and the structural similarity index, and is highly competitive with respect to all present-day distortion-generic NR IQA algorithms.
Journal ArticleDOI
No-reference image quality assessment based on spatial and spectral entropies
TL;DR: It is found that SSEQ matches well with human subjective opinions of image quality, and is statistically superior to the full-reference IQA algorithm SSIM and several top-performing NR IQA methods: BIQI, DIIVINE, and BLIINDS-II.
Journal ArticleDOI
Seven Challenges in Image Quality Assessment: Past, Present, and Future Research
TL;DR: An up-to-date review of research in IQA is provided, and several open challenges in this field are highlighted, including key properties of visual perception, image quality databases, existing full-reference, no- reference, and reduced-reference IQA algorithms.
Journal ArticleDOI
The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement
TL;DR: A novel reduced-reference image quality metric for contrast change (RIQMC) is presented using phase congruency and statistics information of the image histogram and results justify the superiority and efficiency of RIQMC over a majority of classical and state-of-the-art IQA methods.
Journal ArticleDOI
No-Reference Image Blur Assessment Based on Discrete Orthogonal Moments
TL;DR: The experimental results demonstrate that the proposed blind image blur evaluation algorithm can produce blur scores highly consistent with subjective evaluations and outperforms the state-of-the-art image blur metrics and several general-purpose no-reference quality metrics.
References
More filters
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.
Book
Applied Statistics and Probability for Engineers
TL;DR: Montgomery and Runger's Engineering Statistics text as discussed by the authors provides a practical approach oriented to engineering as well as chemical and physical sciences by providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers.
Journal ArticleDOI
Image information and visual quality
Hamid R. Sheikh,Alan C. Bovik +1 more
TL;DR: An image information measure is proposed that quantifies the information that is present in the reference image and how much of this reference information can be extracted from the distorted image and combined these two quantities form a visual information fidelity measure for image QA.
Selection of relevant features and examples in machine
Avrim L. Bluma,Pat Langley +1 more
TL;DR: A survey of machine learning methods for handling data sets containing large amounts of irrelevant information can be found in this article, where the authors focus on two key issues: selecting relevant features and selecting relevant examples.