Journal ArticleDOI
Most apparent distortion: full-reference image quality assessment and the role of strategy
Eric C. Larson,Damon M. Chandler +1 more
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TLDR
A quality assessment method [most apparent distortion (MAD)], which attempts to explicitly model these two separate strategies, local luminance and contrast masking and changes in the local statistics of spatial-frequency components are used to estimate appearance-based perceived distortion in low-quality images.Abstract:
The mainstream approach to image quality assessment has centered around accurately modeling the single most relevant strategy employed by the human visual system (HVS) when judging image quality (e.g., detecting visible differences, and extracting image structure/information). In this work, we suggest that a single strategy may not be sufficient; rather, we advocate that the HVS uses multiple strategies to determine image quality. For images containing near-threshold distortions, the image is most apparent, and thus the HVS attempts to look past the image and look for the distortions (a detection-based strategy). For images containing clearly visible distortions, the distortions are most apparent, and thus the HVS attempts to look past the distortion and look for the image's subject matter (an appearance-based strategy). Here, we present a quality assessment method [most apparent distortion (MAD)], which attempts to explicitly model these two separate strategies. Local luminance and contrast masking are used to estimate detection-based perceived distortion in high-quality images, whereas changes in the local statistics of spatial-frequency components are used to estimate appearance-based perceived distortion in low-quality images. We show that a combination of these two measures can perform well in predicting subjective ratings of image quality.read more
Citations
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Journal ArticleDOI
Screen Content Image Quality Assessment Using Multi-Scale Difference of Gaussian
TL;DR: Experimental results have shown that the proposed IQA model for the SCIs produces high consistency with human perception of the SCI quality and outperforms the state-of-the-art quality models.
Journal ArticleDOI
Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild
TL;DR: A unified BIQA model is developed and an approach of training it for both synthetic and realistic distortions is proposed, and the universality of the proposed training strategy is demonstrated by using it to improve existing BIZA models.
Journal ArticleDOI
KonIQ-10k: Towards an ecologically valid and large-scale IQA database
TL;DR: This work shows how it built an IQA database, KonIQ-10k, consisting of 10,073 images, on which it argues for its ecological validity by analyzing the diversity of the dataset, by comparing it to state-of-the-art IQA databases, and by checking the reliability of user studies.
Journal ArticleDOI
Biologically inspired image quality assessment
TL;DR: A novel IQA approach named biologically inspired feature similarity (BIFS) is proposed, which is demonstrated to be highly consistent with the human perception and outperform state-of-the-art FR-IQA methods across various datasets.
Journal ArticleDOI
New measurements reveal weaknesses of image quality metrics in evaluating graphics artifacts
TL;DR: This work runs two experiments where observers use a brush-painting interface to directly mark image regions with noticeable/objectionable distortions in the presence/absence of a high-quality reference image, respectively, and shows a relatively high correlation between the with-reference and no-reference observer markings.
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.
Proceedings ArticleDOI
Multiscale structural similarity for image quality assessment
TL;DR: This paper proposes a multiscale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions, and develops an image synthesis method to calibrate the parameters that define the relative importance of different scales.
Journal ArticleDOI
Sparse Coding with an Overcomplete Basis Set: A Strategy Employed by V1 ?
TL;DR: These deviations from linearity provide a potential explanation for the weak forms of non-linearity observed in the response properties of cortical simple cells, and they further make predictions about the expected interactions among units in response to naturalistic stimuli.
Journal ArticleDOI
Efficient tests for normality, homoscedasticity and serial independence of regression residuals
Carlos M. Jarque,Anil K. Bera +1 more
TL;DR: In this paper, the Lagrange multiplier procedure is used to derive efficient joint tests for residual normality, homoscedasticity and serial independence, which are simple to compute and asymptotically distributed as χ2.
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.